Publications of year 2021

Books and proceedings

1. Zhi-Hua Zhou. Machine Learning. Springer Singapore, 2021. Keyword(s): Machine Learning, Book on Machine Learning, Computer Science, Learning Algorithms, Neural Networks, Support Vector Machines, Decision Trees, Classification, Clustering, Supervised Learning, Semi-Supervised Learning, Unsupervised Learning, Metric Learning, Feature Selection, Rule Learning, Mathematical Models, Reinforcement Learning, Bayesian Networks, ML, AI, Artificial Intelligence.

   Abstract:

   This is an introductory-level machine learning textbook. To make the content accessible to a wider readership, the author has tried to reduce the use of mathematics. However, to gain a decent understanding of machine learning, basic knowledge of probability, statistics, algebra, optimization, and logic seems unavoidable. Therefore, this book is more appropriate for advanced undergraduate or graduate students in science and engineering, as well as practitioners and researchers with equivalent background knowledge. The book has 16 chapters that can be roughly divided into three parts. The first part includes Chapters 1-3, which introduces the basics of machine learning. The second part includes Chapters 4-10, which presents some classic and popular machine learning methods. The third part includes Chapters 11-16, which covers advanced topics. As a textbook, Chapters 1-9 and 10 can be taught in one semester at the undergraduate level, while the whole book could be used for the graduate level. This introductory textbook aims to cover the core topics of machine learning in one semester, and hence is unable to provide detailed discussions on many important frontier research works. The author believes that, for readers new to this field, it is more important to have a broad view than drill down into the very details. Hence, in-depth discussions are left to advanced courses. However, readers who wish to explore the topics of interest are encouraged to follow the further reading section at the end of each chapter. The book was originally published in Chinese and had a wide readership in the Chinese community. The author would like to thank Dr. Shaowu Liu for his great effort of translating the book into English and thank Springer for the publication.

   
   

   @Book{bookZhiHuaZhou2021MachineLearning,
   author = {Zhi-Hua Zhou},
   publisher = {Springer Singapore},
   title = {Machine Learning},
   year = {2021},
   isbn = {978-981-15-1967-3},
   abstract = {This is an introductory-level machine learning textbook. To make the content accessible to a wider readership, the author has tried to reduce the use of mathematics. However, to gain a decent understanding of machine learning, basic knowledge of probability, statistics, algebra, optimization, and logic seems unavoidable. Therefore, this book is more appropriate for advanced undergraduate or graduate students in science and engineering, as well as practitioners and researchers with equivalent background knowledge. The book has 16 chapters that can be roughly divided into three parts. The first part includes Chapters 1-3, which introduces the basics of machine learning. The second part includes Chapters 4-10, which presents some classic and popular machine learning methods. The third part includes Chapters 11-16, which covers advanced topics. As a textbook, Chapters 1-9 and 10 can be taught in one semester at the undergraduate level, while the whole book could be used for the graduate level. This introductory textbook aims to cover the core topics of machine learning in one semester, and hence is unable to provide detailed discussions on many important frontier research works. The author believes that, for readers new to this field, it is more important to have a broad view than drill down into the very details. Hence, in-depth discussions are left to advanced courses. However, readers who wish to explore the topics of interest are encouraged to follow the further reading section at the end of each chapter. The book was originally published in Chinese and had a wide readership in the Chinese community. The author would like to thank Dr. Shaowu Liu for his great effort of translating the book into English and thank Springer for the publication.},
   doi = {10.1007/978-981-15-1967-3},
   file = {:bookZhiHuaZhou2021MachineLearning.pdf:PDF},
   keywords = {Machine Learning, Book on Machine Learning, Computer Science, Learning Algorithms, Neural Networks, Support Vector Machines, Decision Trees, Classification, Clustering, Supervised Learning, Semi-Supervised Learning, Unsupervised Learning, Metric Learning, Feature Selection, Rule Learning, Mathematical Models, Reinforcement Learning, Bayesian Networks, ML, AI, Artificial Intelligence},
   owner = {ofrey},
   
   }
   

Articles in journal or book chapters

1. Homa Ansari, Francesco De Zan, and Alessandro Parizzi. Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry. IEEE Trans. Geosci. Remote Sens., 59(2):1285-1301, February 2021. Keyword(s): SAR Processing, SAR Interferometry, Time Series, Surface Displacement, Deformation, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, short temporal baseline interferograms, Earth surface deformation, SAR time series, mentioned phase component, biasing impact, quality measure, fading signal, physical signal, modern SAR missions, deformation bias, efficient deformation-signal retrieval, accurate deformation-signal retrieval, multilooked interferograms, systematic bias, measuring surface deformation, SAR interferometry, interferometric signal, multilooked synthetic aperture radar interferograms, atmospheric Earth-surface topography changes, stochastic noise, temporal decorrelation, systematic phase component, Big Data, deformation estimation, differential interferometric synthetic aperture radar, SAR, DInSAR, distributed scatterers, DS, error analysis, near real-time processing, NRT, phase inconsistencies, signal decorrelation, time-series analysis.

   Abstract:

   This article investigates the presence of a new interferometric signal in multilooked synthetic aperture radar (SAR) interferograms that cannot be attributed to the atmospheric or Earth-surface topography changes. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. The presence of such a fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the esti- mation of Earth surface deformation from SAR time series. Here, the contribution of the mentioned phase component is quantita- tively assessed. The biasing impact on the deformation-signal retrieval is further evaluated. A quality measure is introduced to allow the prediction of the associated error with the fading signals. Moreover, a practical solution for the mitigation of this physical signal is discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease significantly. Based on these analyses, we put forward our recommendations for efficient and accurate deformation-signal retrieval from large stacks of multilooked interferograms.

   
   

   @Article{ansariDeZanParizziTGRS2021SystematicBiasInSARInterferometry,
   author = {Ansari, Homa and De Zan, Francesco and Parizzi, Alessandro},
   journal = {IEEE Trans. Geosci. Remote Sens.},
   title = {Study of Systematic Bias in Measuring Surface Deformation With {SAR} Interferometry},
   year = {2021},
   month = feb,
   number = {2},
   pages = {1285-1301},
   volume = {59},
   abstract = {This article investigates the presence of a new interferometric signal in multilooked synthetic aperture radar (SAR) interferograms that cannot be attributed to the atmospheric or Earth-surface topography changes. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. The presence of such a fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the esti- mation of Earth surface deformation from SAR time series. Here, the contribution of the mentioned phase component is quantita- tively assessed. The biasing impact on the deformation-signal retrieval is further evaluated. A quality measure is introduced to allow the prediction of the associated error with the fading signals. Moreover, a practical solution for the mitigation of this physical signal is discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease significantly. Based on these analyses, we put forward our recommendations for efficient and accurate deformation-signal retrieval from large stacks of multilooked interferograms.},
   comment = {See also comments},
   doi = {10.1109/TGRS.2020.3003421},
   file = {:ansariDeZanParizziTGRS2021SystematicBiasInSARInterferometry.pdf:PDF},
   keywords = {SAR Processing, SAR Interferometry, Time Series, Surface Displacement, Deformation, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, short temporal baseline interferograms, Earth surface deformation, SAR time series, mentioned phase component, biasing impact, quality measure, fading signal, physical signal, modern SAR missions, deformation bias, efficient deformation-signal retrieval, accurate deformation-signal retrieval, multilooked interferograms, systematic bias, measuring surface deformation, SAR interferometry, interferometric signal, multilooked synthetic aperture radar interferograms, atmospheric Earth-surface topography changes, stochastic noise, temporal decorrelation, systematic phase component, Big Data, deformation estimation, differential interferometric synthetic aperture radar, SAR, DInSAR, distributed scatterers, DS, error analysis, near real-time processing, NRT, phase inconsistencies, signal decorrelation, time-series analysis},
   owner = {ofrey},
   
   }
   




2. Andreas Baumann-Ouyang, Jemil Avers Butt, David Salido-Monzu, and Andreas Wieser. MIMO-SAR Interferometric Measurements for Structural Monitoring: Accuracy and Limitations. Remote Sensing, 13(21), 2021.

   Abstract:

   Terrestrial Radar Interferometry (TRI) is a measurement technique capable of measuring displacements with high temporal resolution at high accuracy. Current implementations of TRI use large and/or movable antennas for generating two-dimensional displacement maps. Multiple Input Multiple Output Synthetic Aperture Radar (MIMO-SAR) systems are an emerging alternative. As they have no moving parts, they are more easily deployable and cost-effective. These features suggest the potential usage of MIMO-SAR interferometry for structural health monitoring (SHM) supplementing classical geodetic and mechanical measurement systems. The effects impacting the performance of MIMO-SAR systems are, however, not yet sufficiently well understood for practical applications. In this paper, we present an experimental investigation of a MIMO-SAR system originally devised for automotive sensing, and assess its capabilities for deformation monitoring. The acquisitions generated for these investigations feature a 180 deg Field-of-View (FOV), distances of up to 60 m and a temporal sampling rate of up to 400 Hz. Experiments include static and dynamic setups carried out in a lab-environment and under more challenging meteorological conditions featuring sunshine, fog, and cloud-cover. The experiments highlight the capabilities and limitations of the radar, while allowing quantification of the measurement uncertainties, whose sources and impacts we discuss. We demonstrate that, under sufficiently stable meteorological conditions with humidity variations smaller than 1%, displacements as low as 25 um can be detected reliably. Detecting displacements occurring over longer time frames is limited by the uncertainty induced by changes in the refractive index.

   
   

   @Article{baumannButtSalidoMonzuWieserRemoteSensing2021MIMOSARInterferometryAccuracyAndLimitations,
   author = {Baumann-Ouyang, Andreas and Butt, Jemil Avers and Salido-Monzu, David and Wieser, Andreas},
   journal = {Remote Sensing},
   title = {MIMO-SAR Interferometric Measurements for Structural Monitoring: Accuracy and Limitations},
   year = {2021},
   issn = {2072-4292},
   number = {21},
   volume = {13},
   abstract = {Terrestrial Radar Interferometry (TRI) is a measurement technique capable of measuring displacements with high temporal resolution at high accuracy. Current implementations of TRI use large and/or movable antennas for generating two-dimensional displacement maps. Multiple Input Multiple Output Synthetic Aperture Radar (MIMO-SAR) systems are an emerging alternative. As they have no moving parts, they are more easily deployable and cost-effective. These features suggest the potential usage of MIMO-SAR interferometry for structural health monitoring (SHM) supplementing classical geodetic and mechanical measurement systems. The effects impacting the performance of MIMO-SAR systems are, however, not yet sufficiently well understood for practical applications. In this paper, we present an experimental investigation of a MIMO-SAR system originally devised for automotive sensing, and assess its capabilities for deformation monitoring. The acquisitions generated for these investigations feature a 180 deg Field-of-View (FOV), distances of up to 60 m and a temporal sampling rate of up to 400 Hz. Experiments include static and dynamic setups carried out in a lab-environment and under more challenging meteorological conditions featuring sunshine, fog, and cloud-cover. The experiments highlight the capabilities and limitations of the radar, while allowing quantification of the measurement uncertainties, whose sources and impacts we discuss. We demonstrate that, under sufficiently stable meteorological conditions with humidity variations smaller than 1%, displacements as low as 25 um can be detected reliably. Detecting displacements occurring over longer time frames is limited by the uncertainty induced by changes in the refractive index.},
   article-number = {4290},
   doi = {10.3390/rs13214290},
   file = {:baumannButtSalidoMonzuWieserRemoteSensing2021MIMOSARInterferometryAccuracyAndLimitations.pdf:PDF},
   owner = {ofrey},
   url = {https://www.mdpi.com/2072-4292/13/21/4290},
   
   }
   




3. E. Casalini, J. Fagir, and D. Henke. Moving Target Refocusing With the FMCW SAR System MIRANDA-35. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14:1283-1291, 2021. Keyword(s): SAR Processing, Moving Target, Airborne SAR, Synthetic aperture radar, Radar imaging, Earth, Signal processing algorithms, Remote sensing, Radar polarimetry, Motion compensation, Frequency-modulated continuous-wave (FMCW), inverse synthetic aperture radar (ISAR), MIRANDA-35, motion compensation (MoComp), radar imaging, synthetic aperture radar (SAR).

   Abstract:

   Inverse synthetic aperture radar is a commonly adopted technique for producing high-resolution images of moving targets. This article investigates the imaging capabilities of high-frequency and high-bandwidth systems by means of two distinct experiments. The deployed sensor is the Fraunhofer FHR MIRANDA-35, a millimeter-wave synthetic aperture radar airborne system, which transmits frequency-modulated continuous-wave signals at the Ka-band and is capable of achieving centimeter resolution. The performances are assessed by comparing the derived estimates (e.g., radial velocity and acceleration, and dimensions) with independent ground measurements. The resulting accuracy can be summarized as follows: the mean value of the percent error is 2.05% and 2.11% for radial velocity and acceleration, respectively, and 4.27% for the target dimensions.

   
   

   @Article{casaliniFagirHenke2021MovingTargetRefocusingFMCWSARSystemMIRANDA35,
   author = {E. {Casalini} and J. {Fagir} and D. {Henke}},
   journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
   title = {Moving Target Refocusing With the FMCW SAR System MIRANDA-35},
   year = {2021},
   issn = {2151-1535},
   pages = {1283-1291},
   volume = {14},
   abstract = {Inverse synthetic aperture radar is a commonly adopted technique for producing high-resolution images of moving targets. This article investigates the imaging capabilities of high-frequency and high-bandwidth systems by means of two distinct experiments. The deployed sensor is the Fraunhofer FHR MIRANDA-35, a millimeter-wave synthetic aperture radar airborne system, which transmits frequency-modulated continuous-wave signals at the Ka-band and is capable of achieving centimeter resolution. The performances are assessed by comparing the derived estimates (e.g., radial velocity and acceleration, and dimensions) with independent ground measurements. The resulting accuracy can be summarized as follows: the mean value of the percent error is 2.05% and 2.11% for radial velocity and acceleration, respectively, and 4.27% for the target dimensions.},
   doi = {10.1109/JSTARS.2020.3042601},
   file = {:casaliniFagirHenke2021MovingTargetRefocusingFMCWSARSystemMIRANDA35.pdf:PDF},
   keywords = {SAR Processing, Moving Target, Airborne SAR, Synthetic aperture radar;Radar imaging;Earth;Signal processing algorithms;Remote sensing;Radar polarimetry;Motion compensation;Frequency-modulated continuous-wave (FMCW);inverse synthetic aperture radar (ISAR);MIRANDA-35;motion compensation (MoComp);radar imaging;synthetic aperture radar (SAR)},
   owner = {ofrey},
   
   }
   




4. Richard Czikhardt, Hans van der Marel, Freek J. van Leijen, and Ramon F. Hanssen. Estimating Signal-to-Clutter Ratio of InSAR Corner Reflectors From SAR Time Series. IEEE Geoscience and Remote Sensing Letters, pp 1-5, 2021. Keyword(s): SAR Processing, Corner Reflectors, InSAR, SAR Interferometry.

   Abstract:

   The estimation of Signal-to-Clutter Ratio (SCR) of a radar point target, such as a corner reflector, is an essential step for synthetic aperture radar (SAR) interferometry and positioning, as it influences the phase measurement variance as well as the absolute positioning precision. The standard method to estimate the SCR of a point target relies on the debatable assumption of spatial ergodicity, using the clutter of the surrounding as representative of the clutter at the point target. Here, we estimate the SCR of a corner reflector using a time series of SAR measurements, i.e.,\ assuming temporal ergodicity. This assumption is often more realistic, particularly in a complex environment, in the presence of other point scatterers, and for small-sized reflectors. Empirical results on a corner reflector network, using Sentinel-1 SAR measurements, show that the temporal method yields a less biased and more precise estimate of the average SCR. A second experiment shows that the InSAR phase variance as well as positioning precision, predicted using SCR estimated by the temporal estimation method, is closer to the truth.

   
   

   @Article{czikhardtVanDerMarelVanDerLeijenHanssenGRSL2021EstimateSCRofInSARReflectorsFromSARTimeSeries,
   author = {Czikhardt, Richard and van der Marel, Hans and van Leijen, Freek J. and Hanssen, Ramon F.},
   journal = {IEEE Geoscience and Remote Sensing Letters},
   title = {Estimating Signal-to-Clutter Ratio of InSAR Corner Reflectors From SAR Time Series},
   year = {2021},
   issn = {1558-0571},
   pages = {1-5},
   abstract = {The estimation of Signal-to-Clutter Ratio (SCR) of a radar point target, such as a corner reflector, is an essential step for synthetic aperture radar (SAR) interferometry and positioning, as it influences the phase measurement variance as well as the absolute positioning precision. The standard method to estimate the SCR of a point target relies on the debatable assumption of spatial ergodicity, using the clutter of the surrounding as representative of the clutter at the point target. Here, we estimate the SCR of a corner reflector using a time series of SAR measurements, i.e.,\ assuming temporal ergodicity. This assumption is often more realistic, particularly in a complex environment, in the presence of other point scatterers, and for small-sized reflectors. Empirical results on a corner reflector network, using Sentinel-1 SAR measurements, show that the temporal method yields a less biased and more precise estimate of the average SCR. A second experiment shows that the InSAR phase variance as well as positioning precision, predicted using SCR estimated by the temporal estimation method, is closer to the truth.},
   doi = {10.1109/LGRS.2021.3070045},
   file = {:czikhardtVanDerMarelVanDerLeijenHanssenGRSL2021EstimateSCRofInSARReflectorsFromSARTimeSeries.pdf:PDF},
   keywords = {SAR Processing, Corner Reflectors, InSAR, SAR Interferometry},
   owner = {ofrey},
   
   }
   




5. Dyre Oliver Dammann, Mark A. Johnson, Emily R. Fedders, Andrew R. Mahoney, Charles L. Werner, Christopher M. Polashenski, Franz J. Meyer, and Jennifer K. Hutchings. Ground-Based Radar Interferometry of Sea Ice. Remote Sensing, 13(1), 2021.

   Abstract:

   In light of recent Arctic change, there is a need to better understand sea ice dynamic processes at the floe scale to evaluate sea ice stability, deformation, and fracturing. This work investigates the use of the Gamma portable radar interferometer (GPRI) to characterize sea ice displacement and surface topography. We find that the GPRI is best suited to derive lateral surface deformation due to mm-scale horizontal accuracy. We model interferometric phase signatures from sea ice displacement and evaluate possible errors related to noise and antenna motion. We compare the analysis with observations acquired during a drifting ice camp in the Beaufort Sea. We used repeat-scan and stare-mode interferometry to identify two-dimensional shear and to track continuous uni-directional convergence. This paper demonstrates the capacity of the GPRI to derive surface strain on the order of 10−7 and identify different dynamic regions based on sub-mm changes in displacement. The GPRI is thus a promising tool for sea ice applications due to its high accuracy that can potentially resolve pre- and post-fracture deformation relevant to sea ice stability and modeling.

   
   

   @Article{dammannJohnsonFeddersMahoneyWernerPolashenskiMeyerHutchingsREMOTESENSING2021GroundBasedRadarInterferometryOfSeaIce,
   author = {Dammann, Dyre Oliver and Johnson, Mark A. and Fedders, Emily R. and Mahoney, Andrew R. and Werner, Charles L. and Polashenski, Christopher M. and Meyer, Franz J. and Hutchings, Jennifer K.},
   journal = {Remote Sensing},
   title = {Ground-Based Radar Interferometry of Sea Ice},
   year = {2021},
   issn = {2072-4292},
   number = {1},
   volume = {13},
   abstract = {In light of recent Arctic change, there is a need to better understand sea ice dynamic processes at the floe scale to evaluate sea ice stability, deformation, and fracturing. This work investigates the use of the Gamma portable radar interferometer (GPRI) to characterize sea ice displacement and surface topography. We find that the GPRI is best suited to derive lateral surface deformation due to mm-scale horizontal accuracy. We model interferometric phase signatures from sea ice displacement and evaluate possible errors related to noise and antenna motion. We compare the analysis with observations acquired during a drifting ice camp in the Beaufort Sea. We used repeat-scan and stare-mode interferometry to identify two-dimensional shear and to track continuous uni-directional convergence. This paper demonstrates the capacity of the GPRI to derive surface strain on the order of 10−7 and identify different dynamic regions based on sub-mm changes in displacement. The GPRI is thus a promising tool for sea ice applications due to its high accuracy that can potentially resolve pre- and post-fracture deformation relevant to sea ice stability and modeling.},
   article-number = {43},
   doi = {10.3390/rs13010043},
   file = {:dammannJohnsonFeddersMahoneyWernerPolashenskiMeyerHutchingsREMOTESENSING2021GroundBasedRadarInterferometryOfSeaIce.pdf:PDF},
   owner = {ofrey},
   url = {https://www.mdpi.com/2072-4292/13/1/43},
   
   }
   




6. D. Feng, D. An, L. Chen, and X. Huang. Holographic SAR Tomography 3-D Reconstruction Based on Iterative Adaptive Approach and Generalized Likelihood Ratio Test. IEEE Transactions on Geoscience and Remote Sensing, 59(1):305-315, Jan. 2021. Keyword(s): Image resolution, Apertures, Image reconstruction, Signal resolution, Synthetic aperture radar, Tomography, Three-dimensional displays, 3-D imaging, generalized likelihood ratio test (GLRT), holographic synthetic aperture radar (HoloSAR) tomography, iterative adaptive approach (IAA).

   Abstract:

   Holographic synthetic aperture radar (HoloSAR) tomography is an attractive imaging mode that can retrieve the 3-D scattering information of the observed scene over 360 deg azimuth angle variation. To improve the resolution and reduce the sidelobes in elevation, the HoloSAR imaging mode requires many passes in elevation, thus decreasing its feasibility. In this article, an imaging method based on iterative adaptive approach (IAA) and generalized likelihood ratio test (GLRT) is proposed for the HoloSAR with limited elevation passes to achieve super-resolution reconstruction in elevation. For the elevation reconstruction in each range-azimuth cell, the proposed method first adopts the nonparametric IAA to retrieve the elevation profile with improved resolution and suppressed sidelobes. Then, to obtain sparse elevation estimates, the GLRT is used as a model order selection tool to automatically recognize the most likely number of scatterers and obtain the reflectivities of the detected scatterers inside one range-azimuth cell. The proposed method is a super-resolving method. It does not require averaging in range and azimuth, thus it can maintain the range-azimuth resolution. In addition, the proposed method is a user parameter-free method, so it does not need the fine-tuning of any hyperparameters. The super-resolution power and the estimation accuracy of the proposed method are evaluated using the simulated data, and the validity and feasibility of the proposed method are verified by the HoloSAR real data processing results.

   
   

   @Article{fengAnChenHuangTGRS2021HolographicSARTomography,
   author = {D. {Feng} and D. {An} and L. {Chen} and X. {Huang}},
   journal = {IEEE Transactions on Geoscience and Remote Sensing},
   title = {Holographic SAR Tomography 3-D Reconstruction Based on Iterative Adaptive Approach and Generalized Likelihood Ratio Test},
   year = {2021},
   issn = {1558-0644},
   month = {Jan.},
   number = {1},
   pages = {305-315},
   volume = {59},
   abstract = {Holographic synthetic aperture radar (HoloSAR) tomography is an attractive imaging mode that can retrieve the 3-D scattering information of the observed scene over 360 deg azimuth angle variation. To improve the resolution and reduce the sidelobes in elevation, the HoloSAR imaging mode requires many passes in elevation, thus decreasing its feasibility. In this article, an imaging method based on iterative adaptive approach (IAA) and generalized likelihood ratio test (GLRT) is proposed for the HoloSAR with limited elevation passes to achieve super-resolution reconstruction in elevation. For the elevation reconstruction in each range-azimuth cell, the proposed method first adopts the nonparametric IAA to retrieve the elevation profile with improved resolution and suppressed sidelobes. Then, to obtain sparse elevation estimates, the GLRT is used as a model order selection tool to automatically recognize the most likely number of scatterers and obtain the reflectivities of the detected scatterers inside one range-azimuth cell. The proposed method is a super-resolving method. It does not require averaging in range and azimuth, thus it can maintain the range-azimuth resolution. In addition, the proposed method is a user parameter-free method, so it does not need the fine-tuning of any hyperparameters. The super-resolution power and the estimation accuracy of the proposed method are evaluated using the simulated data, and the validity and feasibility of the proposed method are verified by the HoloSAR real data processing results.},
   doi = {10.1109/TGRS.2020.2994201},
   file = {:fengAnChenHuangTGRS2021HolographicSARTomography.pdf:PDF},
   keywords = {Image resolution;Apertures;Image reconstruction;Signal resolution;Synthetic aperture radar;Tomography;Three-dimensional displays;3-D imaging;generalized likelihood ratio test (GLRT);holographic synthetic aperture radar (HoloSAR) tomography;iterative adaptive approach (IAA)},
   owner = {ofrey},
   
   }
   




7. Oriane Gassot, Alain Herique, Wenzhe Fa, Jun Du, and Wlodek Kofman. Ultra-Wideband SAR Tomography on Asteroids. Radio Science, 56(8):e2020RS007186, 2021. Note: E2020RS007186 2020RS007186. Keyword(s): asteroids, Synthetic Aperture Radar, SAR tomography, simulation.

   Abstract:

   Abstract Our knowledge of the internal structure of asteroids is currently indirect and relies on inferences from remote sensing observations of surfaces. However, it is fundamental for understanding small bodies' history and for planetary defense missions. Radar observation of asteroids is the most mature technique available to characterize their inner structure, and Synthetic Aperture Radar Tomography (TomoSAR) allows 3D imaging of their interior. However, as the geometry of observation of small asteroids is complex, and TomoSAR studies have always been performed in the Earth observation geometry, its results in a small body geometry must be simulated to assess the methods' performances. We adopt here two different tomography algorithms and evaluate their performances in our geometry by assessing the resolution and the difference between the scatterer's position and its retrieved position. The first method, the Frequency Domain Back Projection (FDBP) is based on correcting the Fourier transform of the received signal by a phase function built from the geometry. While it can provide a good resolution, a bias remains in the imaged scatterer's position. Meanwhile, Compressive Sensing (CS) relies on the hypothesis that few scatterers lie in the same direction from the subsurface. Its application in the small body geometry is studied, which results in a slightly impoverished resolution but an improved localization of the scatterer.

   
   

   @Article{gassotEtAlRadioScience2021UltraWidebandSARTomographyOnAsteroids,
   author = {Gassot, Oriane and Herique, Alain and Fa, Wenzhe and Du, Jun and Kofman, Wlodek},
   journal = {Radio Science},
   title = {Ultra-Wideband {SAR} Tomography on Asteroids},
   year = {2021},
   note = {e2020RS007186 2020RS007186},
   number = {8},
   pages = {e2020RS007186},
   volume = {56},
   abstract = {Abstract Our knowledge of the internal structure of asteroids is currently indirect and relies on inferences from remote sensing observations of surfaces. However, it is fundamental for understanding small bodies' history and for planetary defense missions. Radar observation of asteroids is the most mature technique available to characterize their inner structure, and Synthetic Aperture Radar Tomography (TomoSAR) allows 3D imaging of their interior. However, as the geometry of observation of small asteroids is complex, and TomoSAR studies have always been performed in the Earth observation geometry, its results in a small body geometry must be simulated to assess the methods' performances. We adopt here two different tomography algorithms and evaluate their performances in our geometry by assessing the resolution and the difference between the scatterer's position and its retrieved position. The first method, the Frequency Domain Back Projection (FDBP) is based on correcting the Fourier transform of the received signal by a phase function built from the geometry. While it can provide a good resolution, a bias remains in the imaged scatterer's position. Meanwhile, Compressive Sensing (CS) relies on the hypothesis that few scatterers lie in the same direction from the subsurface. Its application in the small body geometry is studied, which results in a slightly impoverished resolution but an improved localization of the scatterer.},
   doi = {https://doi.org/10.1029/2020RS007186},
   eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020RS007186},
   file = {:gassotEtAlRadioScience2021UltraWidebandSARTomographyOnAsteroids.pdf:PDF},
   keywords = {asteroids, Synthetic Aperture Radar, SAR tomography, simulation},
   owner = {ofrey},
   url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020RS007186},
   
   }
   




8. Yuta Izumi, Othmar Frey, Simone Baffelli, Irena Hajnsek, and Motoyuki Sato. Efficient Approach for Atmospheric Phase Screen Mitigation in Time Series of Terrestrial Radar Interferometry Data Applied to Measure Glacier Velocity. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14:7734-7750, 2021. Note: Early Access.

   Abstract:

   The accuracy of surface displacements measured by differential radar interferometry is significantly degraded by the atmospheric phase screen (APS). This paper presents a practical and efficient approach for APS mitigation based on the coherent pixels technique (CPT) displacement velocity estimation algorithm. In the proposed approach, all motionless coherent pixels closest to the moving area are defined as seeds surrounding the moving area at the integration step of the CPT. This arrangement consequently minimizes the integration path and the APS effect in the final velocity result. It is designed for terrestrial radar interferometry (TRI) applications. As a continuous operational mode processing framework, a piecewise processing chain is further introduced to derive arbitrary temporal displacement patterns in this work. Three-day datasets measured by Ku-band TRI over a mountainous region in the canton of Valais, Switzerland, were used for validation. Through this validation, a comparative study of five algorithms was carried out. This evaluation showed the efficiency of the proposed approach. The proposed approach does not require phase unwrapping, kriging interpolation, and spatio-temporal covariance inference for APS mitigation, which is appropriate for continuous TRI operation.

   
   

   @Article{izumiFreyBaffelliHajnsekSatoJSTARS2021APSMitigationInTimeSeriesOfTRIDataGlacierVel,
   author = {Yuta Izumi and Othmar Frey and Simone Baffelli and Irena Hajnsek and Motoyuki Sato},
   journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
   title = {Efficient Approach for Atmospheric Phase Screen Mitigation in Time Series of Terrestrial Radar Interferometry Data Applied to Measure Glacier Velocity},
   year = {2021},
   issn = {2151-1535},
   note = {Early Access},
   pages = {7734-7750},
   volume = {14},
   abstract = {The accuracy of surface displacements measured by differential radar interferometry is significantly degraded by the atmospheric phase screen (APS). This paper presents a practical and efficient approach for APS mitigation based on the coherent pixels technique (CPT) displacement velocity estimation algorithm. In the proposed approach, all motionless coherent pixels closest to the moving area are defined as seeds surrounding the moving area at the integration step of the CPT. This arrangement consequently minimizes the integration path and the APS effect in the final velocity result. It is designed for terrestrial radar interferometry (TRI) applications. As a continuous operational mode processing framework, a piecewise processing chain is further introduced to derive arbitrary temporal displacement patterns in this work. Three-day datasets measured by Ku-band TRI over a mountainous region in the canton of Valais, Switzerland, were used for validation. Through this validation, a comparative study of five algorithms was carried out. This evaluation showed the efficiency of the proposed approach. The proposed approach does not require phase unwrapping, kriging interpolation, and spatio-temporal covariance inference for APS mitigation, which is appropriate for continuous TRI operation.},
   doi = {10.1109/JSTARS.2021.3099873},
   file = {:izumiFreyBaffelliHajnsekSatoJSTARS2021APSMitigationInTimeSeriesOfTRIDataGlacierVel.pdf:PDF},
   owner = {ofrey},
   
   }
   




9. D. -H. Jung, D. -H. Kim, M. T. Azim, J. Park, and S. -O. Park. A Novel Signal Processing Technique for Ku-Band Automobile FMCW Fully Polarimetric SAR System Using Triangular LFM. IEEE Transactions on Instrumentation and Measurement, 70:1-10, 2021. Keyword(s): SAR Processing, carborne SAR, Frequency modulation, Signal processing algorithms, Signal processing, Polarimetry, Automobiles, Doppler effect, Synthetic aperture radar, Automobile synthetic aperture radar (SAR), frequency modulated continuous wave (FMCW) radar, fully polarimetric SAR (PolSAR), linear frequency modulation (LFM), range Doppler algorithm (RDA), SAR, triangular waveform.

   Abstract:

   This article presents a novel signal technique for Ku-band automobile frequency-modulated continuous-wave fully polarimetric synthetic aperture radar (FMCW PolSAR) system using triangular linear frequency modulation (LFM). Our proposed system shows the first utilizations of triangular LFM for an FMCW PolSAR. The proposed signal processing algorithm is based on the range Doppler algorithm (RDA). We developed an FMCW PolSAR system that transmits triangular LFM signals, which are used less frequently than sawtooth LFM in an SAR sensor. Using a theoretical background, we describe its configuration and how it works. We propose the novel processing solution, which forms two kinds of single-polarization images from a raw data set and is suitable for our system. We obtained all four kinds of single-polarization images from two raw data sets while using the triangular LFM. In comparison, when using sawtooth LFM, we obtained the four images from four raw data sets by repeating the RDA four times. The proposed method simplifies the FMCW PolSAR system configuration and the processing algorithm. We collected FMCW PolSAR raw data from an experimentally equipped automobile while maintaining a constant speed on a highway. The proposed algorithm and system were validated by processing a high-resolution FMCW PolSAR image.

   
   

   @Article{jungKimAzimParkParkIEEETIM2021KuBandAutomobileFMCWFulPolSARSystem,
   author = {D. -H. {Jung} and D. -H. {Kim} and M. T. {Azim} and J. {Park} and S. -O. {Park}},
   journal = {IEEE Transactions on Instrumentation and Measurement},
   title = {A Novel Signal Processing Technique for {Ku}-Band Automobile {FMCW} Fully Polarimetric {SAR} System Using Triangular {LFM}},
   year = {2021},
   issn = {1557-9662},
   pages = {1-10},
   volume = {70},
   abstract = {This article presents a novel signal technique for Ku-band automobile frequency-modulated continuous-wave fully polarimetric synthetic aperture radar (FMCW PolSAR) system using triangular linear frequency modulation (LFM). Our proposed system shows the first utilizations of triangular LFM for an FMCW PolSAR. The proposed signal processing algorithm is based on the range Doppler algorithm (RDA). We developed an FMCW PolSAR system that transmits triangular LFM signals, which are used less frequently than sawtooth LFM in an SAR sensor. Using a theoretical background, we describe its configuration and how it works. We propose the novel processing solution, which forms two kinds of single-polarization images from a raw data set and is suitable for our system. We obtained all four kinds of single-polarization images from two raw data sets while using the triangular LFM. In comparison, when using sawtooth LFM, we obtained the four images from four raw data sets by repeating the RDA four times. The proposed method simplifies the FMCW PolSAR system configuration and the processing algorithm. We collected FMCW PolSAR raw data from an experimentally equipped automobile while maintaining a constant speed on a highway. The proposed algorithm and system were validated by processing a high-resolution FMCW PolSAR image.},
   doi = {10.1109/TIM.2020.3011601},
   file = {:jungKimAzimParkParkIEEETIM2021KuBandAutomobileFMCWFulPolSARSystem.pdf:PDF},
   keywords = {SAR Processing, carborne SAR, Frequency modulation;Signal processing algorithms;Signal processing;Polarimetry;Automobiles;Doppler effect;Synthetic aperture radar;Automobile synthetic aperture radar (SAR);frequency modulated continuous wave (FMCW) radar;fully polarimetric SAR (PolSAR);linear frequency modulation (LFM);range Doppler algorithm (RDA);SAR;triangular waveform},
   owner = {ofrey},
   
   }
   




10. Da Liang, Kaiyu Liu, Heng Zhang, Yafeng Chen, Haixia Yue, Dacheng Liu, Yunkai Deng, Haoyu Lin, Tingzhu Fang, Chuang Li, and Robert Wang. The Processing Framework and Experimental Verification for the Noninterrupted Synchronization Scheme of LuTan-1. IEEE Transactions on Geoscience and Remote Sensing, 59(7):5740-5750, July 2021. Keyword(s): Synchronization, Oscillators, Satellites, Synthetic aperture radar, Receivers, Remote sensing, Bistatic synthetic aperture radar (BiSAR), internal calibration, noninterrupted, oscillator, phase synchronization.

    Abstract:

    The bistatic synthetic aperture radar (BiSAR) plays an important role in remote sensing. However, the deviation between the two oscillators in BiSAR systems will cause a residual modulation of the echo signal. Therefore, the phase synchronization is an important issue that must be addressed in the BiSAR system. An advanced noninterrupted phase synchronization scheme is used for LuTan-1. The synchronization pulses are exchanged immediately after the ending time of the radar echo receiving window and before the starting time of the next pulse repetition interval, which will not interrupt the normal SAR operation. In order to evaluate the accuracy of the phase synchronization scheme, the model of phase synchronization is introduced at first. The hardware design and processing flow of LuTan-1 are introduced in detail. An innovative internal calibration strategy is also described. Then, the test data acquired by the ground validation system are analyzed to verify the effectiveness of the phase synchronization scheme. The signal-to-noise ratio (SNR) and the synchronization rate are the two most important factors to influence the accuracy in phase synchronization. The conclusions have guiding significance for the synchronization module design of LuTan-1 and the future BiSAR system.

    
    

    @Article{Liang2021,
    author = {Liang, Da and Liu, Kaiyu and Zhang, Heng and Chen, Yafeng and Yue, Haixia and Liu, Dacheng and Deng, Yunkai and Lin, Haoyu and Fang, Tingzhu and Li, Chuang and Wang, Robert},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    title = {The Processing Framework and Experimental Verification for the Noninterrupted Synchronization Scheme of LuTan-1},
    year = {2021},
    issn = {1558-0644},
    month = {July},
    number = {7},
    pages = {5740-5750},
    volume = {59},
    abstract = {The bistatic synthetic aperture radar (BiSAR) plays an important role in remote sensing. However, the deviation between the two oscillators in BiSAR systems will cause a residual modulation of the echo signal. Therefore, the phase synchronization is an important issue that must be addressed in the BiSAR system. An advanced noninterrupted phase synchronization scheme is used for LuTan-1. The synchronization pulses are exchanged immediately after the ending time of the radar echo receiving window and before the starting time of the next pulse repetition interval, which will not interrupt the normal SAR operation. In order to evaluate the accuracy of the phase synchronization scheme, the model of phase synchronization is introduced at first. The hardware design and processing flow of LuTan-1 are introduced in detail. An innovative internal calibration strategy is also described. Then, the test data acquired by the ground validation system are analyzed to verify the effectiveness of the phase synchronization scheme. The signal-to-noise ratio (SNR) and the synchronization rate are the two most important factors to influence the accuracy in phase synchronization. The conclusions have guiding significance for the synchronization module design of LuTan-1 and the future BiSAR system.},
    doi = {10.1109/TGRS.2020.3024561},
    keywords = {Synchronization;Oscillators;Satellites;Synthetic aperture radar;Receivers;Remote sensing;Bistatic synthetic aperture radar (BiSAR);internal calibration;noninterrupted;oscillator;phase synchronization},
    owner = {ofrey},
    
    }
    




11. Giuseppe Parrella, Irena Hajnsek, and Konstantinos P. Papathanassiou. Retrieval of Firn Thickness by Means of Polarisation Phase Differences in L-Band SAR Data. Remote Sensing, 13(21), 2021.

    Abstract:

    The knowledge of glacier zones' extent and their temporal variations is fundamental for the retrieval of surface mass balance of glaciers and ice sheets. In this context, a key parameter is the firn line (FL), the lower boundary of the percolation zone, whose location is an indicator of time-integrated mass balance changes. Several approaches have been developed in the last decades to map the FL by means of Synthetic Aperture Radar (SAR) imagery, mainly exploiting backscatter intensities and their seasonal variation. In this paper, an alternative approach is proposed, based on co-polarisation phase differences (CPDs). In particular, CPDs are interpreted as the result of propagation through anisotropic firn layers and are, therefore, proposed as an indicator of the presence of firn. A model is employed to demonstrate the link between CPDs and firn depth, indicating the potential of polarimetric SAR to improve firn characterization beyond spatial extent and FL detection. The proposed approach is demonstrated on L-band airborne data, acquired on 21 May 2015 by the F-SAR sensor of DLR in West Greenland during the ARCTIC15 campaign, and validated with in-situ information available from other studies.

    
    

    @Article{parrellaHajnsekPapathanassiouRemoteSensing2021RetrievalOfFirnThicknessByCopolarPhaseDifferencesInLBandSARData,
    AUTHOR = {Parrella, Giuseppe and Hajnsek, Irena and Papathanassiou, Konstantinos P.},
    TITLE = {Retrieval of Firn Thickness by Means of Polarisation Phase Differences in {L}-Band {SAR} Data},
    JOURNAL = {Remote Sensing},
    VOLUME = {13},
    YEAR = {2021},
    NUMBER = {21},
    ARTICLE-NUMBER = {4448},
    URL = {https://www.mdpi.com/2072-4292/13/21/4448},
    ISSN = {2072-4292},
    ABSTRACT = {The knowledge of glacier zones' extent and their temporal variations is fundamental for the retrieval of surface mass balance of glaciers and ice sheets. In this context, a key parameter is the firn line (FL), the lower boundary of the percolation zone, whose location is an indicator of time-integrated mass balance changes. Several approaches have been developed in the last decades to map the FL by means of Synthetic Aperture Radar (SAR) imagery, mainly exploiting backscatter intensities and their seasonal variation. In this paper, an alternative approach is proposed, based on co-polarisation phase differences (CPDs). In particular, CPDs are interpreted as the result of propagation through anisotropic firn layers and are, therefore, proposed as an indicator of the presence of firn. A model is employed to demonstrate the link between CPDs and firn depth, indicating the potential of polarimetric SAR to improve firn characterization beyond spatial extent and FL detection. The proposed approach is demonstrated on L-band airborne data, acquired on 21 May 2015 by the F-SAR sensor of DLR in West Greenland during the ARCTIC15 campaign, and validated with in-situ information available from other studies.},
    DOI = {10.3390/rs13214448} 
    }
    




12. S. T. Peters, D. M. Schroeder, M. S. Haynes, D. Castelletti, and A. Romero-Wolf. Passive Synthetic Aperture Radar Imaging Using Radio-Astronomical Sources. IEEE Trans. Geosci. Remote Sens., pp 1-16, 2021. Keyword(s): Synthetic aperture radar, Passive radar, Sun, Radar, Focusing, Signal to noise ratio, Mathematical model, Passive radar, passive radio sounding, passive synthetic aperture radar (SAR), radio echo sounding, Back-Projection, Time-Domain Back-Projection, TDBP.

    Abstract:

    Recent work has demonstrated a passive radio sounding approach that uses the Sun as a source for echo detection and ranging. As the Sun is a moving source with a position that is known a priori, we evaluate this technique's capabilities to measure the echo's phase history, map topography, and perform synthetic aperture radar (SAR) focusing. Here, we present our approach to implementing passive SAR using a compact, temporally incoherent radio-astronomical source as a signal of opportunity. We first evaluate the passive system's capabilities to obtain an echo from a rough surface by determining the critical signal-to-noise ratio (SNR) for reliably observing the Sun's echo reflection with our passive instrument. We then demonstrate that our technique can detect the necessary changes in range, phase, and reflectivity of an echo from the Sun. We next present the experimental results of our passive radar testing using the Sun at Dante's View, Death Valley, to highlight this technique's ability to perform 2-D imaging. Finally, with synthetic data, we demonstrate that we can use time-domain backprojection to focus a planar white noise signal, perform passive SAR imaging, and improve the measurement's SNR and azimuth resolution. The results of passive SAR focusing on white noise highlight the potential for the Sun and Jupiter's radio emissions to perform surface and subsurface imaging for planetary and terrestrial observations.

    
    

    @Article{petersSchroederHaynesCastellettiRomeroWolfTGRS2021PassiveTDBPSARImagingUsingRadioAstronomicalSources,
    author = {S. T. {Peters} and D. M. {Schroeder} and M. S. {Haynes} and D. {Castelletti} and A. {Romero-Wolf}},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    title = {Passive Synthetic Aperture Radar Imaging Using Radio-Astronomical Sources},
    year = {2021},
    issn = {1558-0644},
    pages = {1-16},
    abstract = {Recent work has demonstrated a passive radio sounding approach that uses the Sun as a source for echo detection and ranging. As the Sun is a moving source with a position that is known a priori, we evaluate this technique's capabilities to measure the echo's phase history, map topography, and perform synthetic aperture radar (SAR) focusing. Here, we present our approach to implementing passive SAR using a compact, temporally incoherent radio-astronomical source as a signal of opportunity. We first evaluate the passive system's capabilities to obtain an echo from a rough surface by determining the critical signal-to-noise ratio (SNR) for reliably observing the Sun's echo reflection with our passive instrument. We then demonstrate that our technique can detect the necessary changes in range, phase, and reflectivity of an echo from the Sun. We next present the experimental results of our passive radar testing using the Sun at Dante's View, Death Valley, to highlight this technique's ability to perform 2-D imaging. Finally, with synthetic data, we demonstrate that we can use time-domain backprojection to focus a planar white noise signal, perform passive SAR imaging, and improve the measurement's SNR and azimuth resolution. The results of passive SAR focusing on white noise highlight the potential for the Sun and Jupiter's radio emissions to perform surface and subsurface imaging for planetary and terrestrial observations.},
    doi = {10.1109/TGRS.2021.3050429},
    file = {:petersSchroederHaynesCastellettiRomeroWolfTGRS2021PassiveTDBPSARImagingUsingRadioAstronomicalSources.pdf:PDF},
    keywords = {Synthetic aperture radar;Passive radar;Sun;Radar;Focusing;Signal to noise ratio;Mathematical model;Passive radar;passive radio sounding;passive synthetic aperture radar (SAR);radio echo sounding, Back-Projection, Time-Domain Back-Projection, TDBP},
    owner = {ofrey},
    
    }
    




13. Fabio Rocca, Deren Li, Stefano Tebaldini, Mingsheng Liao, Lu Zhang, Fabrizio Lombardini, Timo Balz, Norbert Haala, Xiaoli Ding, and Ramon Hanssen. Three- and Four-Dimensional Topographic Measurement and Validation. Remote Sensing, 13(15), 2021. Keyword(s): SAR Processing, Synthetic Aperture Radar, Interferometry, SAR Interferometry, Persistent Scatterer Interferometry, PSI, SAR Tomography, Tomography, TomoSAR, 3-D imaging, temporal decorrelation, deformation, validation, surface displacements, topographic mapping.

    Abstract:

    This paper reports on the activities carried out in the context of ''Dragon project 32278: Three- and Four-Dimensional Topographic Measurement and Validation''. The research work was split into three subprojects and encompassed several activities to deliver accurate characterization of targets on land surfaces and deepen the current knowledge on the exploitation of Synthetic Aperture Radar (SAR) data. The goal of Subproject 1 was to validate topographic mapping accuracy of various ESA, TPM, and Chinese satellite system on test sites in the EU and China; define and improve validation methodologies for topographic mapping; and develop and setup test sites for the validation of different surface motion estimation techniques. Subproject 2 focused on the specific case of spatially and temporally decorrelating targets by using multi-baseline interferometric (InSAR) and tomographic (TomoSAR) SAR processing. Research on InSAR led to the development of robust retrieval techniques to estimate target displacement over time. Research on TomoSAR was focused on testing or defining new processing methods for high-resolution 3D imaging of the interior of forests and glaciers and the characterization of their temporal behavior. Subproject 3 was focused on near-real-time motion estimation, considering efficient algorithms for the digestion of new acquisitions and for changes in problem parameterization.

    
    

    @Article{roccaEtREMOTESENSING2021ThreeAnd4DTopographicMeasurementAndValidation,
    author = {Rocca, Fabio and Li, Deren and Tebaldini, Stefano and Liao, Mingsheng and Zhang, Lu and Lombardini, Fabrizio and Balz, Timo and Haala, Norbert and Ding, Xiaoli and Hanssen, Ramon},
    journal = {Remote Sensing},
    title = {Three- and Four-Dimensional Topographic Measurement and Validation},
    year = {2021},
    issn = {2072-4292},
    number = {15},
    volume = {13},
    abstract = {This paper reports on the activities carried out in the context of ''Dragon project 32278: Three- and Four-Dimensional Topographic Measurement and Validation''. The research work was split into three subprojects and encompassed several activities to deliver accurate characterization of targets on land surfaces and deepen the current knowledge on the exploitation of Synthetic Aperture Radar (SAR) data. The goal of Subproject 1 was to validate topographic mapping accuracy of various ESA, TPM, and Chinese satellite system on test sites in the EU and China; define and improve validation methodologies for topographic mapping; and develop and setup test sites for the validation of different surface motion estimation techniques. Subproject 2 focused on the specific case of spatially and temporally decorrelating targets by using multi-baseline interferometric (InSAR) and tomographic (TomoSAR) SAR processing. Research on InSAR led to the development of robust retrieval techniques to estimate target displacement over time. Research on TomoSAR was focused on testing or defining new processing methods for high-resolution 3D imaging of the interior of forests and glaciers and the characterization of their temporal behavior. Subproject 3 was focused on near-real-time motion estimation, considering efficient algorithms for the digestion of new acquisitions and for changes in problem parameterization.},
    article-number = {2861},
    doi = {10.3390/rs13152861},
    file = {:roccaEtREMOTESENSING2021ThreeAnd4DTopographicMeasurementAndValidation.pdf:PDF},
    keywords = {SAR Processing, Synthetic Aperture Radar, Interferometry, SAR Interferometry, Persistent Scatterer Interferometry, PSI, SAR Tomography, Tomography, TomoSAR, 3-D imaging, temporal decorrelation, deformation, validation, surface displacements, topographic mapping},
    url = {https://www.mdpi.com/2072-4292/13/15/2861},
    
    }
    




14. Helmut Rott, Stefan Scheiblauer, Jan Wuite, Lukas Krieger, Dana Floricioiu, Paola Rizzoli, Ludivine Libert, and Thomas Nagler. Penetration of interferometric radar signals in Antarctic snow. The Cryosphere, 15(9):4399-4419, September 2021. Keyword(s): SAR Interferometry, Snow, Arctic Snow.

    Abstract:

    Synthetic aperture radar interferometry (InSAR) is an efficient technique for mapping the surface elevation and its temporal change over glaciers and ice sheets. However, due to the penetration of the SAR signal into snow and ice, the apparent elevation in uncorrected InSAR digital elevation models (DEMs) is displaced versus the actual surface. We studied relations between interferometric radar signals and physical snow properties and tested procedures for correcting the elevation bias. The work is based on satellite and in situ data over Union Glacier in the Ellsworth Mountains, West Antarctica, including interferometric data of the TanDEM-X mission, topographic data from optical satellite sensors and field measurements on snow structure, and stratigraphy undertaken in December 2016. The study area comprises ice- free surfaces, bare ice, dry snow and firn with a variety of structural features related to local differences in wind ex- posure and snow accumulation. Time series of laser measurements of NASA's Ice, Cloud and land Elevation Satellite (ICESat) and ICESat-2 show steady-state surface topography. For area-wide elevation reference we use the Reference Elevation Model of Antarctica (REMA). The different elevation data are vertically co-registered on a blue ice area that is not affected by radar signal penetration. Backscatter simulations with a multilayer radiative transfer model show large variations for scattering of individual snow layers, but the vertical backscatter distribution can be approximated by an exponential function representing uniform absorption and scattering properties. We obtain estimates of the elevation bias by inverting the interferometric volume correlation co- efficient (coherence), applying a uniform volume model for describing the vertical loss function. Whereas the mean values of the computed elevation bias and the elevation difference between the TanDEM-X DEMs and the REMA show good agreement, a trend towards overestimation of penetration is evident for heavily wind-exposed areas with low accumulation and towards underestimation for areas with higher accumulation rates. In both cases deviations from the uniform volume structure are the main reason. In the first case the dense sequence of horizontal structures related to internal wind crust, ice layers and density stratification causes increased scattering in near-surface layers. In the second case the small grain size of the top snow layers causes a downward shift in the scattering phase centre.

    
    

    @Article{rottEtAlCryosphere2021PenetrationOfInSARSignalsInArcticSnow,
    author = {Helmut Rott and Stefan Scheiblauer and Jan Wuite and Lukas Krieger and Dana Floricioiu and Paola Rizzoli and Ludivine Libert and Thomas Nagler},
    journal = {The Cryosphere},
    title = {Penetration of interferometric radar signals in Antarctic snow},
    year = {2021},
    month = {sep},
    number = {9},
    pages = {4399--4419},
    volume = {15},
    abstract = {Synthetic aperture radar interferometry (InSAR) is an efficient technique for mapping the surface elevation and its temporal change over glaciers and ice sheets. However, due to the penetration of the SAR signal into snow and ice, the apparent elevation in uncorrected InSAR digital elevation models (DEMs) is displaced versus the actual surface. We studied relations between interferometric radar signals and physical snow properties and tested procedures for correcting the elevation bias. The work is based on satellite and in situ data over Union Glacier in the Ellsworth Mountains, West Antarctica, including interferometric data of the TanDEM-X mission, topographic data from optical satellite sensors and field measurements on snow structure, and stratigraphy undertaken in December 2016. The study area comprises ice- free surfaces, bare ice, dry snow and firn with a variety of structural features related to local differences in wind ex- posure and snow accumulation. Time series of laser measurements of NASA's Ice, Cloud and land Elevation Satellite (ICESat) and ICESat-2 show steady-state surface topography. For area-wide elevation reference we use the Reference Elevation Model of Antarctica (REMA). The different elevation data are vertically co-registered on a blue ice area that is not affected by radar signal penetration. Backscatter simulations with a multilayer radiative transfer model show large variations for scattering of individual snow layers, but the vertical backscatter distribution can be approximated by an exponential function representing uniform absorption and scattering properties. We obtain estimates of the elevation bias by inverting the interferometric volume correlation co- efficient (coherence), applying a uniform volume model for describing the vertical loss function. Whereas the mean values of the computed elevation bias and the elevation difference between the TanDEM-X DEMs and the REMA show good agreement, a trend towards overestimation of penetration is evident for heavily wind-exposed areas with low accumulation and towards underestimation for areas with higher accumulation rates. In both cases deviations from the uniform volume structure are the main reason. In the first case the dense sequence of horizontal structures related to internal wind crust, ice layers and density stratification causes increased scattering in near-surface layers. In the second case the small grain size of the top snow layers causes a downward shift in the scattering phase centre.},
    doi = {10.5194/tc-15-4399-2021},
    file = {:rottEtAlCryosphere2021PenetrationOfInSARSignalsInArcticSnow.pdf:PDF},
    keywords = {SAR Interferometry, Snow, Arctic Snow},
    owner = {ofrey},
    publisher = {Copernicus {GmbH}},
    
    }
    




15. Emanuele Santi, Marco Brogioni, Marion Leduc-Leballeur, Giovanni Macelloni, Francesco Montomoli, Paolo Pampaloni, Juha Lemmetyinen, Juval Cohen, Helmut Rott, Thomas Nagler, Chris Derksen, Joshua King, Nick Rutter, Richard Essery, Cecile Menard, Melody Sandells, and Michael Kern. Exploiting the ANN Potential in Estimating Snow Depth and Snow Water Equivalent From the Airborne SnowSAR Data at X- and Ku-Bands. IEEE Transactions on Geoscience and Remote Sensing, pp 1-16, 2021. Keyword(s): SAR Processing, Artificial neural networks (ANNs), dense medium radiative transfer (DMRT), quasi Mie scattering (QMS) model, snow depth (SD), snow water equivalent (SWE), SnowSAR, synthetic aperture radar, SAR.

    Abstract:

    Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient R = 0.77 between estimated and target SD, a root-mean-square error (RMSE) = 13 cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with R = 0.74, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount of in situ data required for training the algorithm and of extending the algorithm exportability to other test sites.

    
    

    @Article{santiEtAlTGRS2021ANNPotentialInEstimatingSnowDepthAndSWEfromAirborneSnowSARDataAtXandKuBand,
    author = {Santi, Emanuele and Brogioni, Marco and Leduc-Leballeur, Marion and Macelloni, Giovanni and Montomoli, Francesco and Pampaloni, Paolo and Lemmetyinen, Juha and Cohen, Juval and Rott, Helmut and Nagler, Thomas and Derksen, Chris and King, Joshua and Rutter, Nick and Essery, Richard and Menard, Cecile and Sandells, Melody and Kern, Michael},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    title = {Exploiting the ANN Potential in Estimating Snow Depth and Snow Water Equivalent From the Airborne SnowSAR Data at X- and Ku-Bands},
    year = {2021},
    issn = {1558-0644},
    pages = {1-16},
    abstract = {Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient R = 0.77 between estimated and target SD, a root-mean-square error (RMSE) = 13 cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with R = 0.74, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount of in situ data required for training the algorithm and of extending the algorithm exportability to other test sites.},
    doi = {10.1109/TGRS.2021.3086893},
    file = {:santiEtAlTGRS2021ANNPotentialInEstimatingSnowDepthAndSWEfromAirborneSnowSARDataAtXandKuBand.pdf:PDF},
    keywords = {SAR Processing, Artificial neural networks (ANNs), dense medium radiative transfer (DMRT), quasi Mie scattering (QMS) model, snow depth (SD), snow water equivalent (SWE), SnowSAR, synthetic aperture radar, SAR},
    owner = {ofrey},
    
    }
    




16. Ilgin Seker and Marco Lavalle. Tomographic Performance of Multi-Static Radar Formations: Theory and Simulations. Remote Sensing, 13(4), 2021. Keyword(s): SAR Processing, SAR Tomography, Multibaseline SAR, Multistatic SAR, Simulations, Spaceborne SAR, Airborne SAR.

    Abstract:

    3D imaging of Earth's surface layers (such as canopy, sub-surface, or ice) requires not just the penetration of radar signal into the medium, but also the ability to discriminate multiple scatterers within a slant-range and azimuth resolution cell. The latter requires having multiple radar channels distributed in across-track direction. Here, we describe the theory of multi-static radar tomography with emphasis on resolution, SNR, sidelobes, and nearest ambiguity location vs. platform distribution, observation geometry, and different multi-static modes. Signal-based 1D and 2D simulations are developed and results for various observation geometries, target distributions, acquisition modes, and radar parameters are shown and compared with the theory. Pros and cons of multi-static modes are compared and discussed. Results for various platform formations are shown, revealing that unequal spacing is useful to suppress ambiguities at the cost of increased multiplicative noise. In particular, we demonstrate that the multiple-input multiple-output (MIMO) mode, in combination with nonlinear spacing, outperforms the other modes in terms of ambiguity, sidelobe levels, and noise suppression. These findings are key to guiding the design of tomographic SAR formations for accurate surface topography and vegetation mapping.

    
    

    @Article{sekerLavalleREMOTESENSING2021TomoSARPerformanceForMultiStaticFormationsTheoryAndSimulations,
    author = {Seker, Ilgin and Lavalle, Marco},
    journal = {Remote Sensing},
    title = {Tomographic Performance of Multi-Static Radar Formations: Theory and Simulations},
    year = {2021},
    issn = {2072-4292},
    number = {4},
    volume = {13},
    abstract = {3D imaging of Earth's surface layers (such as canopy, sub-surface, or ice) requires not just the penetration of radar signal into the medium, but also the ability to discriminate multiple scatterers within a slant-range and azimuth resolution cell. The latter requires having multiple radar channels distributed in across-track direction. Here, we describe the theory of multi-static radar tomography with emphasis on resolution, SNR, sidelobes, and nearest ambiguity location vs. platform distribution, observation geometry, and different multi-static modes. Signal-based 1D and 2D simulations are developed and results for various observation geometries, target distributions, acquisition modes, and radar parameters are shown and compared with the theory. Pros and cons of multi-static modes are compared and discussed. Results for various platform formations are shown, revealing that unequal spacing is useful to suppress ambiguities at the cost of increased multiplicative noise. In particular, we demonstrate that the multiple-input multiple-output (MIMO) mode, in combination with nonlinear spacing, outperforms the other modes in terms of ambiguity, sidelobe levels, and noise suppression. These findings are key to guiding the design of tomographic SAR formations for accurate surface topography and vegetation mapping.},
    article-number = {737},
    doi = {10.3390/rs13040737},
    file = {:sekerLavalleREMOTESENSING2021TomoSARPerformanceForMultiStaticFormationsTheoryAndSimulations.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Multibaseline SAR, Multistatic SAR, Simulations, Spaceborne SAR, Airborne SAR},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/13/4/737},
    
    }
    




17. Dario Tagliaferri, Mattia Brambilla, Monica Nicoli, and Umberto Spagnolini. Sensor-Aided Beamwidth and Power Control for Next Generation Vehicular Communications. IEEE Access, 9:56301-56317, 2021. Keyword(s): Degradation, Power control, Sensor systems, Sensors, Trajectory, Vehicle dynamics, Global Positioning System, Beam pointing, beam tracking, beamwidth and power control, on-board sensors, V2X.

    Abstract:

    Ultra-reliable low-latency Vehicle-to-Everything (V2X) communications are needed to meet the extreme requirements of enhanced driving applications. Millimeter-Wave (24.25-52.6 GHz) or sub-THz (>100 GHz) V2X communications are a viable solution, provided that the highly collimated beams are kept aligned during vehicles' maneuverings. In this work, we propose a sensor-assisted dynamic Beamwidth and Power Control (BPC) system to counteract the detrimental effect of vehicle dynamics, exploiting data collected by on-board inertial and positioning sensors, mutually exchanged among vehicles over a parallel low-rate link, e.g., 5G New Radio (NR) Frequency Range 1 (FR1). The proposed BPC solution works on top of a sensor-aided Beam Alignment and Tracking (BAT) system, overcoming the limitations of fixed-beamwidth systems and optimizing the performance in challenging Vehicle-to-Vehicle (V2V) scenarios, even if extensions to Vehicle-to-Infrastructure (V2I) use-cases are feasible. We evaluate the sensor-assisted dynamic BPC by simulation over real trajectories and sensors' data collected by a dedicated experimental campaign. The goal is to show the advantages of the proposed BPC strategy in a high data-rate Line-Of-Sight (LOS) V2V context, and to outline the requirements in terms of sensors' sampling time and accuracy, along with the end-to-end latency on the control channel.

    
    

    @ARTICLE{tagliaferriBrambillaNicoliSpagnoliniIEEEACCESS2021SensorAidedBeamwidthAndPowerControlForVehicularCommunications,
    author={Tagliaferri, Dario and Brambilla, Mattia and Nicoli, Monica and Spagnolini, Umberto},
    journal={IEEE Access},
    title={Sensor-Aided Beamwidth and Power Control for Next Generation Vehicular Communications},
    year={2021},
    volume={9},
    number={},
    pages={56301-56317},
    abstract={Ultra-reliable low-latency Vehicle-to-Everything (V2X) communications are needed to meet the extreme requirements of enhanced driving applications. Millimeter-Wave (24.25-52.6 GHz) or sub-THz (>100 GHz) V2X communications are a viable solution, provided that the highly collimated beams are kept aligned during vehicles' maneuverings. In this work, we propose a sensor-assisted dynamic Beamwidth and Power Control (BPC) system to counteract the detrimental effect of vehicle dynamics, exploiting data collected by on-board inertial and positioning sensors, mutually exchanged among vehicles over a parallel low-rate link, e.g., 5G New Radio (NR) Frequency Range 1 (FR1). The proposed BPC solution works on top of a sensor-aided Beam Alignment and Tracking (BAT) system, overcoming the limitations of fixed-beamwidth systems and optimizing the performance in challenging Vehicle-to-Vehicle (V2V) scenarios, even if extensions to Vehicle-to-Infrastructure (V2I) use-cases are feasible. We evaluate the sensor-assisted dynamic BPC by simulation over real trajectories and sensors' data collected by a dedicated experimental campaign. The goal is to show the advantages of the proposed BPC strategy in a high data-rate Line-Of-Sight (LOS) V2V context, and to outline the requirements in terms of sensors' sampling time and accuracy, along with the end-to-end latency on the control channel.},
    keywords={Degradation;Power control;Sensor systems;Sensors;Trajectory;Vehicle dynamics;Global Positioning System;Beam pointing;beam tracking;beamwidth and power control;on-board sensors;V2X},
    doi={10.1109/ACCESS.2021.3071726},
    ISSN={2169-3536},
    
    }
    




18. Dario Tagliaferri, Marco Rizzi, Monica Nicoli, Stefano Tebaldini, Ivan Russo, Andrea Virgilio Monti-Guarnieri, Claudio Maria Prati, and Umberto Spagnolini. Navigation-Aided Automotive SAR for High-Resolution Imaging of Driving Environments. IEEE Access, 9:35599-35615, 2021. Keyword(s): Spaceborne radar, Radar imaging, Sensor systems, Sensors, Synthetic aperture radar, Standards, Automotive engineering, Sensor fusion, automotive SAR, environment mapping, ADAS, in-car navigation, IMU/GNSS integration.

    Abstract:

    The evolution of Advanced Driver Assistance Systems (ADAS) towards the ultimate goal of autonomous driving relies on a conspicuous number of sensors, to perform a wide range of operations, from parking assistance to emergency braking and environment mapping for target recognition/classification. Low-cost Mass-Market Radars (MMRs) are today widely used for object detection at various ranges (up to 250 meters) but they might not be suited for high-precision environment mapping. In this context, vehicular Synthetic Aperture Radar (SAR) is emerging as a promising technique to augment radar imaging capability by exploiting the vehicle motion to provide two-dimensional (2D), or even three-dimensional (3D), images of the surroundings. SAR has a higher resolution compared to standard automotive radars, provided that motion is precisely known. In this regard, one of the most attractive solutions to increase the positioning accuracy is to fuse the information from multiple on-board sensors, such as Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), odometers and steering angle sensors. This paper proposes a multi-sensor fusion technique to support automotive SAR systems, experimentally validating the approach and demonstrating its advantages compared to standard navigation solutions. The results show that multi-sensor-aided SAR images the surrounding with centimeter-level accuracy over typical urban trajectories, confirming its potential for practical applications and leaving room for further improvements.

    
    

    @ARTICLE{tagliaferriEtAlIEEEAccess2021NavigationAidedAutomotiveSARForHighResolutionImagingDrivingEnvironments,
    author={Tagliaferri, Dario and Rizzi, Marco and Nicoli, Monica and Tebaldini, Stefano and Russo, Ivan and Monti-Guarnieri, Andrea Virgilio and Prati, Claudio Maria and Spagnolini, Umberto},
    journal={IEEE Access},
    title={Navigation-Aided Automotive SAR for High-Resolution Imaging of Driving Environments},
    year={2021},
    volume={9},
    number={},
    pages={35599-35615},
    abstract={The evolution of Advanced Driver Assistance Systems (ADAS) towards the ultimate goal of autonomous driving relies on a conspicuous number of sensors, to perform a wide range of operations, from parking assistance to emergency braking and environment mapping for target recognition/classification. Low-cost Mass-Market Radars (MMRs) are today widely used for object detection at various ranges (up to 250 meters) but they might not be suited for high-precision environment mapping. In this context, vehicular Synthetic Aperture Radar (SAR) is emerging as a promising technique to augment radar imaging capability by exploiting the vehicle motion to provide two-dimensional (2D), or even three-dimensional (3D), images of the surroundings. SAR has a higher resolution compared to standard automotive radars, provided that motion is precisely known. In this regard, one of the most attractive solutions to increase the positioning accuracy is to fuse the information from multiple on-board sensors, such as Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), odometers and steering angle sensors. This paper proposes a multi-sensor fusion technique to support automotive SAR systems, experimentally validating the approach and demonstrating its advantages compared to standard navigation solutions. The results show that multi-sensor-aided SAR images the surrounding with centimeter-level accuracy over typical urban trajectories, confirming its potential for practical applications and leaving room for further improvements.},
    keywords={Spaceborne radar;Radar imaging;Sensor systems;Sensors;Synthetic aperture radar;Standards;Automotive engineering;Sensor fusion;automotive SAR;environment mapping;ADAS;in-car navigation;IMU/GNSS integration},
    doi={10.1109/ACCESS.2021.3062084},
    ISSN={2169-3536},
    month={},
    
    }
    




19. S. Vey, D. Al-Halbouni, M.H. Haghighi, F. Alshawaf, J. Vüllers, A. Güntner, G. Dick, M. Ramatschi, P. Teatini, J. Wickert, and M. Weber. Delayed subsidence of the Dead Sea shore due to hydro-meteorological changes. Scientific Reports, 11(1), 2021. Note: Cited By 0.
    

    @ARTICLE{Vey2021,
    author={Vey, S. and Al-Halbouni, D. and Haghighi, M.H. and Alshawaf, F. and Vüllers, J. and Güntner, A. and Dick, G. and Ramatschi, M. and Teatini, P. and Wickert, J. and Weber, M.},
    title={Delayed subsidence of the Dead Sea shore due to hydro-meteorological changes},
    journal={Scientific Reports},
    year={2021},
    volume={11},
    number={1},
    doi={10.1038/s41598-021-91949-y},
    art_number={13518},
    note={cited By 0},
    url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109016085&doi=10.1038%2fs41598-021-91949-y&partnerID=40&md5=6e75a86a1313a50f5bfaa89f68e37d2d},
    document_type={Article},
    source={Scopus},
    
    }
    




20. Marwan Younis, Felipe Queiroz de Almeida, Michelangelo Villano, Sigurd Huber, Gerhard Krieger, and Alberto Moreira. Digital Beamforming for Spaceborne Reflector-Based Synthetic Aperture Radar, Part 1: Basic imaging modes. IEEE Geoscience and Remote Sensing Magazine, 9(3):8-25, Sep. 2021. Keyword(s): SCORE, scan-on-receive, SweepSAR, Digital Beamforming, Beamforming, Wide-Swath, Synthetic aperture radar, Spaceborne SAR, Mission Concept, Antenna Concept, Imaging Concept, Antenna feeds, Transmission line measurements, Reflector antennas, Spaceborne radar, Radar imaging, Parabolic antennas, Tandem-L, Rose-L, NiSAR.

    Abstract:

    Deployable reflector antennas illuminated by a digital feed array enable spaceborne synthetic aperture radar (SAR) systems to image an ultrawide, continuous swath at a fine azimuth resolution. This is facilitated by the use of dedicated imaging modes and by multidimensional digital beamforming (DBF) techniques. This article is part 1 of a tutorial trilogy, where a focus is put on the required onboard functionality, operational techniques, and DBF aspects, for which a rigorous mathematical description is included. To maintain general validity, the functional implementation for the various modes is detailed, thus avoiding restricting the description to a specific realization. The reader is assumed to be familiar with the general concept of SAR and, otherwise, referred to the literature on the topic. The approach followed in the trilogy is to start with a basic imaging concept and then move to more advanced modes, thus successively increasing the complexity; the mathematical description follows the same approach.

    
    

    @Article{younisEtAlIEEEGRSM2021DigitalBeamformingForSpaceborneReflectorBasedSyntheticApertureRadarPart1,
    author = {Younis, Marwan and de Almeida, Felipe Queiroz and Villano, Michelangelo and Huber, Sigurd and Krieger, Gerhard and Moreira, Alberto},
    journal = {IEEE Geoscience and Remote Sensing Magazine},
    title = {Digital Beamforming for Spaceborne Reflector-Based Synthetic Aperture Radar, Part 1: Basic imaging modes},
    year = {2021},
    issn = {2168-6831},
    month = {Sep.},
    number = {3},
    pages = {8-25},
    volume = {9},
    abstract = {Deployable reflector antennas illuminated by a digital feed array enable spaceborne synthetic aperture radar (SAR) systems to image an ultrawide, continuous swath at a fine azimuth resolution. This is facilitated by the use of dedicated imaging modes and by multidimensional digital beamforming (DBF) techniques. This article is part 1 of a tutorial trilogy, where a focus is put on the required onboard functionality, operational techniques, and DBF aspects, for which a rigorous mathematical description is included. To maintain general validity, the functional implementation for the various modes is detailed, thus avoiding restricting the description to a specific realization. The reader is assumed to be familiar with the general concept of SAR and, otherwise, referred to the literature on the topic. The approach followed in the trilogy is to start with a basic imaging concept and then move to more advanced modes, thus successively increasing the complexity; the mathematical description follows the same approach.},
    doi = {10.1109/MGRS.2021.3060543},
    file = {:younisEtAlIEEEGRSM2021DigitalBeamformingForSpaceborneReflectorBasedSyntheticApertureRadarPart1.pdf:PDF},
    keywords = {SCORE, scan-on-receive, SweepSAR, Digital Beamforming, Beamforming, Wide-Swath, Synthetic aperture radar, Spaceborne SAR, Mission Concept, Antenna Concept, Imaging Concept, Antenna feeds, Transmission line measurements, Reflector antennas, Spaceborne radar, Radar imaging, Parabolic antennas, Tandem-L, Rose-L, NiSAR},
    
    }
    




21. P. Yuan, A. Hunegnaw, F. Alshawaf, J. Awange, A. Klos, F.N. Teferle, and H. Kutterer. Feasibility of ERA5 integrated water vapor trends for climate change analysis in continental Europe: An evaluation with GPS (1994–2019) by considering statistical significance. Remote Sensing of Environment, 260, 2021. Note: Cited By 7.
    

    @ARTICLE{Yuan2021,
    author={Yuan, P. and Hunegnaw, A. and Alshawaf, F. and Awange, J. and Klos, A. and Teferle, F.N. and Kutterer, H.},
    title={Feasibility of ERA5 integrated water vapor trends for climate change analysis in continental Europe: An evaluation with GPS (1994–2019) by considering statistical significance},
    journal={Remote Sensing of Environment},
    year={2021},
    volume={260},
    doi={10.1016/j.rse.2021.112416},
    art_number={112416},
    note={cited By 7},
    url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105320875&doi=10.1016%2fj.rse.2021.112416&partnerID=40&md5=7415cca7f7c367e78c705812b164804e},
    document_type={Article},
    source={Scopus},
    
    }
    




22. Howard Zebker. Accuracy of a Model-Free Algorithm for Temporal InSAR Tropospheric Correction. Remote Sensing, 13(3), 2021. Keyword(s): SAR Processing, Interferometry, SAR Interferometry, DInSAR, InSAR, atmosphere, troposphere, APS, atmospheric phase screen, correction, atmospheric correction, tropospheric correction, path delay, tropospheric path delay, time series, deformation, displacement, deformation monitoring, monitoring.

    Abstract:

    Atmospheric propagational phase variations are the dominant source of error for InSAR (interferometric synthetic aperture radar) time series analysis, generally exceeding uncertainties from poor signal to noise ratio or signal correlation. The spatial properties of these errors have been well studied, but, to date, their temporal dependence and correction have received much less attention. Here, we present an evaluation of the magnitude of tropospheric artifacts in derived time series after compensation using an algorithm that requires only the InSAR data. The level of artifact reduction equals or exceeds that from many weather model-based methods, while avoiding the need to globally access fine-scale atmosphere parameters at all times. Our method consists of identifying all points in an InSAR stack with consistently high correlation and computing, and then removing, a fit of the phase at each of these points with respect to elevation. A comparison with GPS truth yields a reduction of three, from a rms misfit of 5–6 to ~2 cm over time. This algorithm can be readily incorporated into InSAR processing flows without the need for outside information.

    
    

    @Article{zebkerRemoteSensing2021AccuracyOfModelFreeTemporalInSARTroposphericCorrection,
    author = {Zebker, Howard},
    journal = {Remote Sensing},
    title = {Accuracy of a Model-Free Algorithm for Temporal {InSAR} Tropospheric Correction},
    year = {2021},
    issn = {2072-4292},
    number = {3},
    volume = {13},
    abstract = {Atmospheric propagational phase variations are the dominant source of error for InSAR (interferometric synthetic aperture radar) time series analysis, generally exceeding uncertainties from poor signal to noise ratio or signal correlation. The spatial properties of these errors have been well studied, but, to date, their temporal dependence and correction have received much less attention. Here, we present an evaluation of the magnitude of tropospheric artifacts in derived time series after compensation using an algorithm that requires only the InSAR data. The level of artifact reduction equals or exceeds that from many weather model-based methods, while avoiding the need to globally access fine-scale atmosphere parameters at all times. Our method consists of identifying all points in an InSAR stack with consistently high correlation and computing, and then removing, a fit of the phase at each of these points with respect to elevation. A comparison with GPS truth yields a reduction of three, from a rms misfit of 5–6 to ~2 cm over time. This algorithm can be readily incorporated into InSAR processing flows without the need for outside information.},
    article-number = {409},
    doi = {10.3390/rs13030409},
    file = {:zebkerRemoteSensing2021AccuracyOfModelFreeTemporalInSARTroposphericCorrection.pdf:PDF},
    keywords = {SAR Processing, Interferometry, SAR Interferometry, DInSAR, InSAR, atmosphere, troposphere, APS, atmospheric phase screen, correction, atmospheric correction, tropospheric correction, path delay, tropospheric path delay, time series, deformation, displacement, deformation monitoring, monitoring},
    owner = {ofrey},
    url = {https://www.mdpi.com/2072-4292/13/3/409},
    
    }
    




23. Yanyan Zhang, Hao Zhang, Shuai Hou, Yunkai Deng, Weidong Yu, and Robert Wang. An Innovative Superpolyhedron (SP) Formation for Multistatic SAR (M-SAR) Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 59(12):10136-10150, December 2021. Keyword(s): Satellites, Synthetic aperture radar, Spaceborne radar, Radar, Space vehicles, Sea measurements, Radar imaging, Genetic algorithm (GA), interferometric synthetic aperture radar (InSAR), multistatic synthetic aperture radar (M-SAR), satellite formation, superpolyhedron (SP).

    Abstract:

    Spaceborne multistatic synthetic aperture radar (M-SAR) has extensive applications, including multiangle imaging, digital beamforming (DBF) and cross- and along-track interferometry. However, it is difficult for classical satellite formations to meet the multimission (e.g., cross-track interferometry and along-track interferometry, i.e., XTI and ATI) requirements of M-SAR concurrently. Therefore, superpolyhedron (SP), an innovative satellite formation based on the dual-helix and pendulum formations, is proposed to maximize the coverage ratio of the effective cross- and along-track interferometric baselines at the same time. A method of constructing the SP formation is detailed. The method is a three-step procedure, in which the first two steps aim at obtaining an initial formation via exploiting the geometry of the formation dynamics; the last step solves an optimization problem. Then, the design of a supertetrahedron (ST) formation, a special case of the SP formation, is investigated as a numerical example. The merit of SP formation is represented as the coverage ratios of effective cross- and along-track interferometric baselines. The result is compared with those of the classical satellite formations. It shows that only the coverage ratios of the ST formation are greater than 70% simultaneously. Therefore, the ST formation can realize both effective XTI and ATI. It implies that the SP formation has the potential to be used in future spaceborne M-SAR interferometry.

    
    

    @Article{Zhang2021,
    author = {Zhang, Yanyan and Zhang, Hao and Hou, Shuai and Deng, Yunkai and Yu, Weidong and Wang, Robert},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    title = {An Innovative Superpolyhedron (SP) Formation for Multistatic SAR (M-SAR) Interferometry},
    year = {2021},
    issn = {1558-0644},
    month = {Dec},
    number = {12},
    pages = {10136-10150},
    volume = {59},
    abstract = {Spaceborne multistatic synthetic aperture radar (M-SAR) has extensive applications, including multiangle imaging, digital beamforming (DBF) and cross- and along-track interferometry. However, it is difficult for classical satellite formations to meet the multimission (e.g., cross-track interferometry and along-track interferometry, i.e., XTI and ATI) requirements of M-SAR concurrently. Therefore, superpolyhedron (SP), an innovative satellite formation based on the dual-helix and pendulum formations, is proposed to maximize the coverage ratio of the effective cross- and along-track interferometric baselines at the same time. A method of constructing the SP formation is detailed. The method is a three-step procedure, in which the first two steps aim at obtaining an initial formation via exploiting the geometry of the formation dynamics; the last step solves an optimization problem. Then, the design of a supertetrahedron (ST) formation, a special case of the SP formation, is investigated as a numerical example. The merit of SP formation is represented as the coverage ratios of effective cross- and along-track interferometric baselines. The result is compared with those of the classical satellite formations. It shows that only the coverage ratios of the ST formation are greater than 70% simultaneously. Therefore, the ST formation can realize both effective XTI and ATI. It implies that the SP formation has the potential to be used in future spaceborne M-SAR interferometry.},
    doi = {10.1109/TGRS.2021.3051727},
    keywords = {Satellites;Synthetic aperture radar;Spaceborne radar;Radar;Space vehicles;Sea measurements;Radar imaging;Genetic algorithm (GA);interferometric synthetic aperture radar (InSAR);multistatic synthetic aperture radar (M-SAR);satellite formation;superpolyhedron (SP)},
    owner = {ofrey},
    
    }
    

Conference articles

1. Davide Castelletti, Gordon Farquharson, Craig Stringham, Michael Duersch, and Duncan Eddy. Capella Space First Operational SAR Satellite. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, pages 1483-1486, July 2021.

   Abstract:

   Capella Space launched its first commercial Synthetic Aperture Radar (SAR) satellite in August 2020. After commissioning phase, Capella started commercial operations in January 2021, deploying a fully-functional SAR system that demonstrates three engineering milestones: an 8-m2 deployable reflector mounted on small and agile satellite; the capability to process and timely deliver 0.5 m resolution spotlight images with 9 looks; and an automated tasking and delivery system that simplifies the ordering of high-quality SAR imagery for expert and novice users. In this paper, we present results from the commissioning and calibration/validation operations. We also compare images collected with the variety of imaging modes that Capella systems can collect.

   
   

   @InProceedings{castellettiEtAlIGARSS2021CapellaSpaceFirstOperationalSARSatellite,
   author = {Castelletti, Davide and Farquharson, Gordon and Stringham, Craig and Duersch, Michael and Eddy, Duncan},
   booktitle = {2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS},
   title = {Capella Space First Operational SAR Satellite},
   year = {2021},
   month = {July},
   pages = {1483-1486},
   abstract = {Capella Space launched its first commercial Synthetic Aperture Radar (SAR) satellite in August 2020. After commissioning phase, Capella started commercial operations in January 2021, deploying a fully-functional SAR system that demonstrates three engineering milestones: an 8-m2 deployable reflector mounted on small and agile satellite; the capability to process and timely deliver 0.5 m resolution spotlight images with 9 looks; and an automated tasking and delivery system that simplifies the ordering of high-quality SAR imagery for expert and novice users. In this paper, we present results from the commissioning and calibration/validation operations. We also compare images collected with the variety of imaging modes that Capella systems can collect.},
   doi = {10.1109/IGARSS47720.2021.9554100},
   file = {:castellettiEtAlIGARSS2021CapellaSpaceFirstOperationalSARSatellite.pdf:PDF},
   issn = {2153-7003},
   owner = {ofrey},
   
   }
   




2. C. Derksen, J. King, S. Belair, C. Garnaud, V. Vionnet, V Fortin, J. Lemmetyinen, Y. Crevier, P. Plourde, B. Lawrence, H. van Mierlo, G. Burbidge, and P. Siqueira. Development of the Terrestrial Snow Mass Mission. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 614-617, July 2021. IEEE. Keyword(s): Radar Remote Sensing, snow, Terrestrial Snow Mass Mission, TSMM, Ku-band, Ka-band.

   Abstract:

   For northern countries like Canada, seasonal snow cover is a key component of the water cycle and a commodity of high importance to public safety, economic sustainability, and ecosystem function. Despite this importance, snow water equivalent (SWE - the amount of water stored by snow) information from existing surface observing networks and satellite data does not adequately address most user needs. To address this gap, a new synthetic aperture radar (SAR) mission capable of providing information on terrestrial SWE at previously unrealized spatial resolution is currently under development. The Terrestrial Snow Mass Mission (?TSMM?) will provide moderate resolution (500m) dual frequency (13.5/17.25 GHz) Ku-band radar measurements across all northern hemisphere snow covered areas every 7 days. Data from this mission will be used at Environment and Climate Change Canada to (1) provide a new level of information on the temporal/spatial variability in SWE in support of climate services, and (2) feed into environmental prediction and analysis systems to improve weather and hydrological forecasts.

   
   

   @InProceedings{derksenEtAl2021DevelopmentOfTheTerrestrialSnowMassMissionTSMM,
   author = {C. Derksen and J. King and S. Belair and C. Garnaud and V. Vionnet and V Fortin and J. Lemmetyinen and Y. Crevier and P. Plourde and B. Lawrence and H. van Mierlo and G. Burbidge and P. Siqueira},
   booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
   title = {Development of the Terrestrial Snow Mass Mission},
   year = {2021},
   month = jul,
   pages = {614-617},
   publisher = {IEEE},
   abstract = {For northern countries like Canada, seasonal snow cover is a key component of the water cycle and a commodity of high importance to public safety, economic sustainability, and ecosystem function. Despite this importance, snow water equivalent (SWE - the amount of water stored by snow) information from existing surface observing networks and satellite data does not adequately address most user needs. To address this gap, a new synthetic aperture radar (SAR) mission capable of providing information on terrestrial SWE at previously unrealized spatial resolution is currently under development. The Terrestrial Snow Mass Mission (?TSMM?) will provide moderate resolution (500m) dual frequency (13.5/17.25 GHz) Ku-band radar measurements across all northern hemisphere snow covered areas every 7 days. Data from this mission will be used at Environment and Climate Change Canada to (1) provide a new level of information on the temporal/spatial variability in SWE in support of climate services, and (2) feed into environmental prediction and analysis systems to improve weather and hydrological forecasts.},
   doi = {10.1109/IGARSS47720.2021.9553496},
   keywords = {Radar Remote Sensing, snow, Terrestrial Snow Mass Mission, TSMM, Ku-band, Ka-band},
   owner = {ofrey},
   
   }
   




3. Gordon Farquharson, Davide Castelletti, Craig Stringham, and Duncan Eddy. An Update on the Capella Space Radar Constellation. In EUSAR 2021; 13th European Conference on Synthetic Aperture Radar, pages 1-4, March 2021.

   Abstract:

   We present an update on the Capella synthetic aperture radar constellation. Analysis of the performance of the radar is discussed and sample imagery collected is shown. We find that the imagery meets or exceeds pre-launch spatial resolution and radiometric goals.

   
   

   @InProceedings{farquharsonCastellettiStringhamEddyEUSAR2021UpdateOnCapellaSpaceRadarConstellation,
   author = {Farquharson, Gordon and Castelletti, Davide and Stringham, Craig and Eddy, Duncan},
   booktitle = {EUSAR 2021; 13th European Conference on Synthetic Aperture Radar},
   title = {An Update on the Capella Space Radar Constellation},
   year = {2021},
   month = {March},
   pages = {1-4},
   abstract = {We present an update on the Capella synthetic aperture radar constellation. Analysis of the performance of the radar is discussed and sample imagery collected is shown. We find that the imagery meets or exceeds pre-launch spatial resolution and radiometric goals.},
   file = {:farquharsonCastellettiStringhamEddyEUSAR2021UpdateOnCapellaSpaceRadarConstellation.pdf:PDF},
   owner = {ofrey},
   url = {https://ieeexplore.ieee.org/document/9554100},
   
   }
   




4. Othmar Frey and Charles L. Werner. UAV-borne repeat-pass SAR interferometry and SAR tomography with a compact L-band SAR system. In Proc. Europ. Conf. Synthetic Aperture Radar, EUSAR, pages 181-184, March 2021. VDE. Keyword(s): SAR Processing, UAV, SAR Tomography, Time-Domain Back-projection, TDBP, GPU, mobile mapping, surface displacements, mobile mapping of surface displacements, landslide, geohazard mapping.

   Abstract:

   In this contribution, we present SAR image focusing, interferometric, and first tomographic processing results computed from repeat-pass SAR data sets acquired on-board of a vertical-take-off-and-landing (VTOL) unmanned aerial vehicle (UAV): the data was acquired using a novel compact FMCW L-band SAR system in two repeat-pass SAR campaigns flown on 2019-02-13 and 2019-03-28, respectively. In these demonstration campaigns, the Gamma L-band SAR system was deployed and operated on Aeroscout's VTOL UAV Scout B1-100. Repeat-pass interferograms and coherence maps with a temporal baseline of up to 43 days are presented and a tomographic profile obtained from short-term repeat-pass measurements is shown. The results demonstrate the feasibility of UAV-borne repeat-pass SAR interferometry and SAR tomography at L-band

   
   

   @InProceedings{freyWernerEUSAR2021UAVborneRepeatPassSARInterferometryAndSARTomography,
   author = {Frey,Othmar and Werner, Charles L.},
   booktitle = {Proc. Europ. Conf. Synthetic Aperture Radar, EUSAR},
   title = {{UAV}-borne repeat-pass {SAR} interferometry and {SAR} tomography with a compact {L}-band {SAR} system},
   year = {2021},
   month = {March},
   pages = {181-184},
   publisher = {VDE},
   abstract = {In this contribution, we present SAR image focusing, interferometric, and first tomographic processing results computed from repeat-pass SAR data sets acquired on-board of a vertical-take-off-and-landing (VTOL) unmanned aerial vehicle (UAV): the data was acquired using a novel compact FMCW L-band SAR system in two repeat-pass SAR campaigns flown on 2019-02-13 and 2019-03-28, respectively. In these demonstration campaigns, the Gamma L-band SAR system was deployed and operated on Aeroscout's VTOL UAV Scout B1-100. Repeat-pass interferograms and coherence maps with a temporal baseline of up to 43 days are presented and a tomographic profile obtained from short-term repeat-pass measurements is shown. The results demonstrate the feasibility of UAV-borne repeat-pass SAR interferometry and SAR tomography at L-band},
   file = {:freyWernerEUSAR2021UAVborneRepeatPassSARInterferometryAndSARTomography.pdf:PDF},
   isbn = {978-3-8007-5457-1},
   keywords = {SAR Processing, UAV, SAR Tomography, Time-Domain Back-projection, TDBP, GPU, mobile mapping, surface displacements, mobile mapping of surface displacements, landslide, geohazard mapping},
   owner = {ofrey},
   url = {https://ieeexplore.ieee.org/document/9472527},
   
   }
   




5. Othmar Frey, Charles L. Werner, Andrea Manconi, and Roberto Coscione. Measurement of surface displacements with a UAV-borne/car-borne L-band DInSAR system: system performance and use cases. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 628-631, 2021. IEEE. Keyword(s): SAR Processing, SAR interferometry, mobile mapping, car-borne SAR, UAV, airborne SAR, surface displacements, landslide, geohazard, monitoring, terrestrial radar interferometer, back- projection, GPU, CUDA, interferometry, L-band, INS, GNSS.

   Abstract:

   In this paper, we present examples of DInSAR-based measurement of surface displacements using a novel compact L-band SAR system that can be mounted on mobile mapping platforms such as a UAV or a car. The good DInSAR system performance is demonstrated and, particularly, we also show a use case in which a car-borne system setup is employed to map surface displacements of a fast-moving landslide and the surrounding area in Switzerland. Our results show that car-borne and UAV-borne interferometric displacement measurements at L-band are feasible with high quality over various natural terrain. This novel compact DInSAR system for agile platforms complements existing terrestrial, airborne, and space-borne radar interferometry systems in terms of its new combination of (1) radar wavelength (sensitivity to displacement/decorrelation properties), (2) spatial resolution, (3) (near-) terrestrial observation geometry, and (4) mobile mapping capability.

   
   

   @InProceedings{freyEtAlIGARSS2021UAVandCarborneDinSARwithGammaLbandSAR,
   author = {Frey, Othmar and Werner, Charles L. and Manconi, Andrea and Coscione, Roberto},
   booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
   title = {Measurement of surface displacements with a {UAV}-borne/car-borne {L}-band {DInSAR} system: system performance and use cases},
   year = {2021},
   pages = {628-631},
   publisher = {IEEE},
   abstract = {In this paper, we present examples of DInSAR-based measurement of surface displacements using a novel compact L-band SAR system that can be mounted on mobile mapping platforms such as a UAV or a car. The good DInSAR system performance is demonstrated and, particularly, we also show a use case in which a car-borne system setup is employed to map surface displacements of a fast-moving landslide and the surrounding area in Switzerland. Our results show that car-borne and UAV-borne interferometric displacement measurements at L-band are feasible with high quality over various natural terrain. This novel compact DInSAR system for agile platforms complements existing terrestrial, airborne, and space-borne radar interferometry systems in terms of its new combination of (1) radar wavelength (sensitivity to displacement/decorrelation properties), (2) spatial resolution, (3) (near-) terrestrial observation geometry, and (4) mobile mapping capability.},
   doi = {10.1109/IGARSS47720.2021.9553573},
   file = {:freyEtAlIGARSS2021UAVandCarborneDinSARwithGammaLbandSAR.pdf:PDF},
   keywords = {SAR Processing, SAR interferometry, mobile mapping, car-borne SAR, UAV, airborne SAR, surface displacements, landslide, geohazard, monitoring, terrestrial radar interferometer, back- projection, GPU, CUDA, interferometry, L-band, INS, GNSS},
   
   }
   




6. Silvan Leinss, Shiyi Li, and Othmar Frey. Measuring Glacier Velocity by Autofocusing Temporally Multilooked SAR Time Series. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 5493-5496, July 2021. IEEE.

   Abstract:

   ABSTRACT SAR offset tracking, applied on areas with strong temporal decorrelation, requires relatively large image templates for cross-correlation to compensate for incoherent radar speckle. Template edge lengths of 64-12 pixels are common. Furthermore, velocity maps are often incomplete because weakly visible features are obscured by uncorrelated speckle. To improve SAR offset tracking, we propose a new robust method which can significantly enhance both the spatial completeness and the resolution of velocity products by assuming a stationary velocity field. The method minimizes the motion blur of moving features which occurs when SAR backscatter time se- ries are multilooked in time. Our velocity-adaptive temporal multilooking strongly reduces speckle without losing spatial resolution which makes the cross-correlation much more ro- bust even for template sizes as small as 30 x 30 pixels. We demonstrate the method by generating a high resolution velocity map of Great Aletsch Glacier in Switzerland.

   
   

   @InProceedings{leinssLiFreyIGARSS2021GlacierVelocityByAutofocusingTemporallyMultilookedSARTimeSeries,
   author = {Leinss, Silvan and Li, Shiyi and Frey, Othmar},
   booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
   title = {Measuring Glacier Velocity by Autofocusing Temporally Multilooked {SAR} Time Series},
   year = {2021},
   month = jul,
   pages = {5493-5496},
   publisher = {IEEE},
   abstract = {ABSTRACT SAR offset tracking, applied on areas with strong temporal decorrelation, requires relatively large image templates for cross-correlation to compensate for incoherent radar speckle. Template edge lengths of 64-12 pixels are common. Furthermore, velocity maps are often incomplete because weakly visible features are obscured by uncorrelated speckle. To improve SAR offset tracking, we propose a new robust method which can significantly enhance both the spatial completeness and the resolution of velocity products by assuming a stationary velocity field. The method minimizes the motion blur of moving features which occurs when SAR backscatter time se- ries are multilooked in time. Our velocity-adaptive temporal multilooking strongly reduces speckle without losing spatial resolution which makes the cross-correlation much more ro- bust even for template sizes as small as 30 x 30 pixels. We demonstrate the method by generating a high resolution velocity map of Great Aletsch Glacier in Switzerland.},
   doi = {10.1109/IGARSS47720.2021.9554999},
   file = {:leinssLiFreyIGARSS2021GlacierVelocityByAutofocusingTemporallyMultilookedSARTimeSeries.pdf:PDF},
   owner = {ofrey},
   
   }
   




7. Andrew Rittenbach and John Paul Walters. Demonstration of a fully neural network based synthetic aperture radar processing pipeline for image formation and analysis. In Sachidananda R. Babu, Arnaud Hélière, and Toshiyoshi Kimura, editors, Sensors, Systems, and Next-Generation Satellites XXV, volume 11858, pages 98 - 109, 2021. International Society for Optics and Photonics, SPIE. Keyword(s): SAR Processing, synthetic aperture radar, onboard processing, SAR image formation and analysis, deep learning based image formation, AI, machine learning, azimuth focusing.

   Abstract:

   Synthetic Aperture Radar (SAR) imaging systems operate by emitting radar signals from a moving object, such as a satellite, towards the target of interest. Reflected radar echoes are received and later used by image formation algorithms to form a SAR image. There is great interest in using SAR images in computer vision tasks such as classification or automatic target recognition. Today, however, SAR applications consist of multiple operations: image formation followed by image processing. In this work, we train a deep neural network that performs both the image formation and image processing tasks, integrating the SAR processing pipeline. Results show that our integrated pipeline can output accurately classified SAR imagery with image quality comparable to those formed using a traditional algorithm, showing that fully neural network based SAR processing pipeline is feasible.

   
   

   @InProceedings{rittenbachWaltersSPIE2021NeuralNetworkBasedSARProcessingForImageFormationAndAnalysis,
   author = {Rittenbach, Andrew and Walters, John Paul},
   booktitle = {Sensors, Systems, and Next-Generation Satellites XXV},
   title = {{Demonstration of a fully neural network based synthetic aperture radar processing pipeline for image formation and analysis}},
   year = {2021},
   editor = {Sachidananda R. Babu and Arnaud Hélière and Toshiyoshi Kimura},
   organization = {International Society for Optics and Photonics},
   pages = {98 -- 109},
   publisher = {SPIE},
   volume = {11858},
   abstract = {Synthetic Aperture Radar (SAR) imaging systems operate by emitting radar signals from a moving object, such as a satellite, towards the target of interest. Reflected radar echoes are received and later used by image formation algorithms to form a SAR image. There is great interest in using SAR images in computer vision tasks such as classification or automatic target recognition. Today, however, SAR applications consist of multiple operations: image formation followed by image processing. In this work, we train a deep neural network that performs both the image formation and image processing tasks, integrating the SAR processing pipeline. Results show that our integrated pipeline can output accurately classified SAR imagery with image quality comparable to those formed using a traditional algorithm, showing that fully neural network based SAR processing pipeline is feasible.},
   doi = {10.1117/12.2599955},
   file = {:rittenbachWaltersSPIE2021NeuralNetworkBasedSARProcessingForImageFormationAndAnalysis.pdf:PDF},
   keywords = {SAR Processing, synthetic aperture radar, onboard processing, SAR image formation and analysis, deep learning based image formation, AI, machine learning, azimuth focusing},
   url = {https://doi.org/10.1117/12.2599955},
   
   }
   




8. Marcel Stefko, Othmar Frey, Charles Werner, and Irena Hajnsek. KAPRI: a Bistatic Full-Polarimetric Interferometric Real-Aperture Radar System for Monitoring of Natural Environments. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 1950-1953, 2021. IEEE. Keyword(s): SAR Processing, WBSCAT, Wide-band Scatterometer, ESA, European Space Agency, Snow, ESA Snowlab, Wideband Scatterometer, WBScat, microwave scatterometer, aperture synthesis, time series, polarimetry, tomography, SAR tomography.
   

   @InProceedings{stefkoFreyWernerHajnsekIGARSS2021KAPRIBistaticPolInterferoRealApertureSystem,
   author = {Stefko, Marcel and Frey, Othmar and Werner, Charles and Hajnsek, Irena},
   booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
   title = {KAPRI: a Bistatic Full-Polarimetric Interferometric Real-Aperture Radar System for Monitoring of Natural Environments},
   year = {2021},
   pages = {1950-1953},
   publisher = {IEEE},
   doi = {10.1109/IGARSS47720.2021.9553427},
   file = {:stefkoFreyWernerHajnsekIGARSS2021KAPRIBistaticPolInterferoRealApertureSystem:PDF;:stefkoFreyWernerHajnsekIGARSS2021KAPRIBistaticPolInterferoRealApertureSystem.pdf:PDF},
   keywords = {SAR Processing, WBSCAT, Wide-band Scatterometer, ESA, European Space Agency, Snow, ESA Snowlab, Wideband Scatterometer, WBScat, microwave scatterometer, aperture synthesis, time series, polarimetry, tomography, SAR tomography},
   owner = {ofrey},
   
   }
   




9. Dario Tagliaferri, Marco Rizzi, Stefano Tebaldini, Monica Nicoli, Ivan Russo, Christian Mazzucco, Andrea Virgilio Monti-Guarnieri, Claudio Maria Prati, and Umberto Spagnolini. Cooperative Synthetic Aperture Radar in an Urban Connected Car Scenario. In 2021 1st IEEE International Online Symposium on Joint Communications Sensing (JC S), pages 1-4, February 2021. Keyword(s): Image resolution, Bandwidth, Radar imaging, Radar polarimetry, Sensors, Synthetic aperture radar, Automotive engineering, Multi-vehicle SAR, Cooperative SAR, Environment Mapping, Joint Communication and Sensing.

   Abstract:

   With the raising interest in automated driving, onboard perception systems are required to perform a wide range of functionalities, from basic emergency braking to mapping of the surroundings. However, current automotive radars are known to suffer from low angular/range resolution and might be unable to meet the high-definition mapping required by high levels of automation. Synthetic Aperture Radar (SAR) systems allow to improve the angular resolution of standard automotive radars, but their imaging performance is constrained by the available bandwidth. In Joint Communication and Sensing (JCS), where the on-board radio is used also to inter-connect road users, cooperation enables SAR performance augmentation thanks to the improved geometric factor, especially for near-isotropic targets (poles, pedestrians, etc.). Furthermore, the combination of communication and sensing allows to trade between bandwidth, cooperation and synthetic aperture so as to optimize the overall JCS performance. In this paper, we propose a cooperative SAR (C-SAR) system for automotive scenarios, where single ego-vehicle SAR images are exchanged with neighboring vehicles thus combined to enhance SAR performance. Preliminary simulations support the proposed idea, enabling SAR imaging improvements in low bandwidth scenarios.

   
   

   @INPROCEEDINGS{tagliaferriEtAlConf2021CooperativeSARinUrbanConnectedCarScenario,
   author={Tagliaferri, Dario and Rizzi, Marco and Tebaldini, Stefano and Nicoli, Monica and Russo, Ivan and Mazzucco, Christian and Monti-Guarnieri, Andrea Virgilio and Prati, Claudio Maria and Spagnolini, Umberto},
   booktitle={2021 1st IEEE International Online Symposium on Joint Communications Sensing (JC S)},
   title={Cooperative Synthetic Aperture Radar in an Urban Connected Car Scenario},
   year={2021},
   volume={},
   number={},
   pages={1-4},
   abstract={With the raising interest in automated driving, onboard perception systems are required to perform a wide range of functionalities, from basic emergency braking to mapping of the surroundings. However, current automotive radars are known to suffer from low angular/range resolution and might be unable to meet the high-definition mapping required by high levels of automation. Synthetic Aperture Radar (SAR) systems allow to improve the angular resolution of standard automotive radars, but their imaging performance is constrained by the available bandwidth. In Joint Communication and Sensing (JCS), where the on-board radio is used also to inter-connect road users, cooperation enables SAR performance augmentation thanks to the improved geometric factor, especially for near-isotropic targets (poles, pedestrians, etc.). Furthermore, the combination of communication and sensing allows to trade between bandwidth, cooperation and synthetic aperture so as to optimize the overall JCS performance. In this paper, we propose a cooperative SAR (C-SAR) system for automotive scenarios, where single ego-vehicle SAR images are exchanged with neighboring vehicles thus combined to enhance SAR performance. Preliminary simulations support the proposed idea, enabling SAR imaging improvements in low bandwidth scenarios.},
   keywords={Image resolution;Bandwidth;Radar imaging;Radar polarimetry;Sensors;Synthetic aperture radar;Automotive engineering;Multi-vehicle SAR;Cooperative SAR;Environment Mapping;Joint Communication and Sensing},
   doi={10.1109/JCS52304.2021.9376348},
   ISSN={},
   month={Feb},
   
   }
   




10. Charles Werner, Othmar Frey, Reza Naderpour, Andreas Wiesmann, Martin Süss, and Urs Wegmuller. Aperture Synthesis and Calibration of the WBSCAT Ground-Based Scatterometer. In Proc. IEEE Int. Geosci. Remote Sens. Symp., pages 1947-1950, 2021. IEEE. Keyword(s): SAR Processing, WBSCAT, Wide-band Scatterometer, ESA, European Space Agency, Snow, ESA Snowlab, Wideband Scatterometer, WBScat, microwave scatterometer, aperture synthesis, time series, polarimetry, tomography, SAR tomography.
    

    @InProceedings{wernerFreyNaderpourWiesmannSussWegmullerIGARSS2021ApertureSynthesisAndCalibrationOfWBSCAT,
    author = {Werner, Charles and Frey, Othmar and Naderpour, Reza and Wiesmann, Andreas and S\"uss, Martin and Wegmuller, Urs},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    title = {Aperture Synthesis and Calibration of the {WBSCAT} Ground-Based Scatterometer},
    year = {2021},
    pages = {1947-1950},
    publisher = {IEEE},
    doi = {10.1109/IGARSS47720.2021.9554592},
    file = {:wernerFreyNaderpourWiesmannSussWegmullerIGARSS2021ApertureSynthesisAndCalibrationOfWBSCAT.pdf:PDF},
    keywords = {SAR Processing, WBSCAT, Wide-band Scatterometer, ESA, European Space Agency, Snow, ESA Snowlab, Wideband Scatterometer, WBScat, microwave scatterometer, aperture synthesis, time series, polarimetry, tomography, SAR tomography},
    owner = {ofrey},
    
    }
    

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